Triple
T8741898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yamal Airlines |
E207522
|
entity |
| Predicate | ICAO airline designator |
P36333
|
FINISHED |
| Object | LLM |
E207522
|
NE FINISHED |
How this triple was built (2 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: LLM | Statement: [Yamal Airlines, ICAO airline designator, LLM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LLM Context triple: [Yamal Airlines, ICAO airline designator, LLM]
-
A.
LLM
chosen
LLM is the ICAO airline designator assigned to Yamal Airlines, a Russian regional carrier.
-
B.
LLaMA
LLaMA is a family of large language models developed by Meta AI, designed for efficient training and inference across a range of natural language processing tasks.
-
C.
AI21 Labs
AI21 Labs is an artificial intelligence company specializing in large language models and advanced natural language processing technologies.
-
D.
PaLM 2
PaLM 2 is a large-scale language model developed by Google, known for powering various AI features across Google products before being succeeded by the Gemini family of models.
-
E.
GPT-Neo
GPT-Neo is an open-source family of autoregressive language models developed by EleutherAI as a free alternative to OpenAI’s GPT-3.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca835a03a081909d4d4cd01a18c9fb |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d6fd5dc8190906b7147f27c5d46 |
completed | March 31, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf518750948190a42ad8fc352ac851 |
completed | April 3, 2026, 5:35 a.m. |
Created at: March 30, 2026, 6:38 p.m.