Triple
T3520111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allen Institute for Artificial Intelligence |
E74400
|
entity |
| Predicate | hasResearchProgram |
P3
|
FINISHED |
| Object |
AllenNLP research
AllenNLP research is a natural language processing research program focused on developing state-of-the-art models, tools, and methodologies for understanding and generating human language.
|
E366089
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: AllenNLP research | Statement: [Allen Institute for Artificial Intelligence, hasResearchProgram, AllenNLP research]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AllenNLP research Context triple: [Allen Institute for Artificial Intelligence, hasResearchProgram, AllenNLP research]
-
A.
Exploring the Limits of Language Modeling
"Exploring the Limits of Language Modeling" is a research paper that investigates how far large-scale neural language models can be pushed in terms of performance, scalability, and generalization on natural language tasks.
-
B.
Distributed Representations of Sentences and Documents
"Distributed Representations of Sentences and Documents" is a seminal machine learning paper that introduced the Paragraph Vector (Doc2Vec) method for learning continuous vector representations of variable-length text such as sentences, paragraphs, and documents.
-
C.
Allen Institute for Artificial Intelligence
The Allen Institute for Artificial Intelligence is a research organization founded by Paul Allen that focuses on advancing artificial intelligence through high-impact scientific and engineering efforts, including open research, tools, and datasets.
-
D.
Hugging Face Transformers
Hugging Face Transformers is a widely used open-source library that provides state-of-the-art transformer-based models and tools for natural language processing and related machine learning tasks.
-
E.
LLM
LLM is the ICAO airline designator assigned to Yamal Airlines, a Russian regional carrier.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: AllenNLP research Triple: [Allen Institute for Artificial Intelligence, hasResearchProgram, AllenNLP research]
Generated description
AllenNLP research is a natural language processing research program focused on developing state-of-the-art models, tools, and methodologies for understanding and generating human language.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AllenNLP research Target entity description: AllenNLP research is a natural language processing research program focused on developing state-of-the-art models, tools, and methodologies for understanding and generating human language.
-
A.
Exploring the Limits of Language Modeling
"Exploring the Limits of Language Modeling" is a research paper that investigates how far large-scale neural language models can be pushed in terms of performance, scalability, and generalization on natural language tasks.
-
B.
Distributed Representations of Sentences and Documents
"Distributed Representations of Sentences and Documents" is a seminal machine learning paper that introduced the Paragraph Vector (Doc2Vec) method for learning continuous vector representations of variable-length text such as sentences, paragraphs, and documents.
-
C.
Allen Institute for Artificial Intelligence
The Allen Institute for Artificial Intelligence is a research organization founded by Paul Allen that focuses on advancing artificial intelligence through high-impact scientific and engineering efforts, including open research, tools, and datasets.
-
D.
Hugging Face Transformers
Hugging Face Transformers is a widely used open-source library that provides state-of-the-art transformer-based models and tools for natural language processing and related machine learning tasks.
-
E.
LLM
LLM is the ICAO airline designator assigned to Yamal Airlines, a Russian regional carrier.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc4af70c8190a7471f28e1efd7fd |
completed | March 8, 2026, 6:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e848d1c8190b100cb2e1218afbb |
completed | March 13, 2026, 3:03 a.m. |
| NEDg | Description generation | batch_69b37f07ab70819089fdb7083b81b992 |
completed | March 13, 2026, 3:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b38078bc288190b69d73a64acce8ca |
completed | March 13, 2026, 3:11 a.m. |
Created at: March 8, 2026, 3:19 p.m.