Triple
T9899269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azure Cognitive Services |
E182244
|
entity |
| Predicate | includesService |
P1393
|
FINISHED |
| Object |
Personalizer
Personalizer is an Azure Cognitive Service that uses reinforcement learning to deliver personalized, context-aware content and experiences in real time.
|
E828318
|
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: Personalizer | Statement: [Azure Cognitive Services, includesService, Personalizer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Personalizer Context triple: [Azure Cognitive Services, includesService, Personalizer]
-
A.
Ray Tune
Ray Tune is a scalable hyperparameter tuning and experiment management library for machine learning, built on the Ray distributed computing framework.
-
B.
Favoriten
Favoriten is the 10th district of Vienna, Austria, known as a large, densely populated residential area with a diverse population and a mix of historic and modern urban development.
-
C.
Butter Beck
Butter Beck is a small stream in northern England that serves as a tributary of the River Esk.
-
D.
Justify
Justify is an American Thoroughbred racehorse best known for winning the 2018 Triple Crown.
-
E.
Grok
Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
- 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: Personalizer Triple: [Azure Cognitive Services, includesService, Personalizer]
Generated description
Personalizer is an Azure Cognitive Service that uses reinforcement learning to deliver personalized, context-aware content and experiences in real time.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Personalizer Target entity description: Personalizer is an Azure Cognitive Service that uses reinforcement learning to deliver personalized, context-aware content and experiences in real time.
-
A.
Ray Tune
Ray Tune is a scalable hyperparameter tuning and experiment management library for machine learning, built on the Ray distributed computing framework.
-
B.
Favoriten
Favoriten is the 10th district of Vienna, Austria, known as a large, densely populated residential area with a diverse population and a mix of historic and modern urban development.
-
C.
Butter Beck
Butter Beck is a small stream in northern England that serves as a tributary of the River Esk.
-
D.
Justify
Justify is an American Thoroughbred racehorse best known for winning the 2018 Triple Crown.
-
E.
Grok
Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
- 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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4adc03481909e0f657db01e5bab |
completed | April 2, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb1b9534819093c5150f1ed8f685 |
completed | April 5, 2026, 4:54 a.m. |
| NEDg | Description generation | batch_69d1ecb3e4a08190add9b971d96f331d |
completed | April 5, 2026, 5:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1ed413edc81908177be16d5127a58 |
completed | April 5, 2026, 5:04 a.m. |
Created at: March 30, 2026, 8:40 p.m.