Triple
T9139479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aeromar |
E219285
|
entity |
| Predicate | ICAO airline designator |
P36333
|
FINISHED |
| Object | TAO |
E219285
|
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: TAO | Statement: [Aeromar, ICAO airline designator, TAO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TAO Context triple: [Aeromar, ICAO airline designator, TAO]
-
A.
TAO
chosen
TAO is the ICAO airline designator assigned to Aeromar, a regional airline based in Mexico.
-
B.
TAO
TAO is the UN/LOCODE designation for the major Chinese seaport of Qingdao, a key hub for international maritime trade.
-
C.
TAU
TAU is a major public research university located in Tel Aviv, Israel, known for its strong programs across science, engineering, humanities, and the arts.
-
D.
TAI
TAI is the high-precision time standard used worldwide as the basis for civil timekeeping and scientific measurements.
-
E.
TAI
TAI is the ICAO airline designator assigned to TACA Airlines, a major Central American carrier.
- 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_69ca83e012288190a5771058adbaabd2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8f129c08190b6f053984cb7363f |
completed | April 1, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0480458348190b0b87f7a66d85b87 |
completed | April 3, 2026, 11:06 p.m. |
Created at: March 30, 2026, 7:19 p.m.