Triple
T6382284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coleman A. Young International Airport |
E143612
|
entity |
| Predicate | FAAIdentifier |
P420
|
FINISHED |
| Object | DET |
E118882
|
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: DET | Statement: [Coleman A. Young International Airport, FAAIdentifier, DET]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DET Context triple: [Coleman A. Young International Airport, FAAIdentifier, DET]
-
A.
DET
chosen
DET is the standard NHL abbreviation for the Detroit Red Wings professional ice hockey team.
-
B.
DEN
DEN is the three-letter IATA airport code for Denver International Airport, the primary commercial airport serving Denver, Colorado.
-
C.
tet
tet is the ISO 639-1 language code for Tetum, an Austronesian language spoken primarily in East Timor.
-
D.
DED
DED is the commonly used abbreviation for the ASME Design Engineering Division, a professional group within ASME focused on advancing the field of mechanical design engineering.
-
E.
De
De is the given name of Zhu De, a prominent Chinese Communist military leader and one of the founders of the People’s Liberation Army.
- 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_69c008dac1ec81909cef8157ccd69962 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0685385948190938b67bff671072b |
completed | March 22, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c63874aba88190a543f21e968fbc06 |
completed | March 27, 2026, 7:57 a.m. |
Created at: March 22, 2026, 4:34 p.m.