Triple
T34261110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | served by Ector County Airport facilities |
E879033
|
entity |
| Predicate | IATAServiceCode |
P2569
|
FINISHED |
| Object | MAF |
—
|
NE NERFINISHED |
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: MAF | Statement: [served by Ector County Airport facilities, IATAServiceCode, MAF]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: IATAServiceCode Context triple: [served by Ector County Airport facilities, IATAServiceCode, MAF]
-
A.
IATAcode
Indicates the three-letter IATA airport or airline code assigned to the entity.
-
B.
hasIATAcode
chosen
Indicates that an entity, typically a transportation facility like an airport, is associated with a specific IATA (International Air Transport Association) code.
-
C.
ICAOcode
Indicates that an entity is identified by a specific four-letter airport or aerodrome code assigned by the International Civil Aviation Organization (ICAO).
-
D.
ICAOCodeCS300
Indicates that an entity has the ICAO aircraft type designator corresponding to the CS300 aircraft model.
-
E.
icaoCodeType
Indicates that the relationship specifies or classifies the ICAO (International Civil Aviation Organization) code associated with an entity.
- F. None of above.
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_69f349b421cc8190b4b4655e1d612548 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71362f1448190985a80ce7af475cb |
completed | May 3, 2026, 9:20 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:56 a.m.