Triple
T4407072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 5 (O'Hare) |
E93759
|
entity |
| Predicate | airportCodeOfParent |
P17503
|
FINISHED |
| Object | ORD |
—
|
LITERAL 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: ORD | Statement: [Terminal 5 (O'Hare), airportCodeOfParent, ORD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportCodeOfParent Context triple: [Terminal 5 (O'Hare), airportCodeOfParent, ORD]
-
A.
ICAOcode
Indicates that an entity is identified by a specific four-letter airport or aerodrome code assigned by the International Civil Aviation Organization (ICAO).
-
B.
hasAirportCodeCity
Indicates that a city is associated with a specific airport code (such as an IATA or ICAO code) that identifies its airport.
-
C.
airportIATAAssociated
chosen
Indicates that an airport is associated with a specific IATA (International Air Transport Association) code.
-
D.
IATAcode
Indicates the three-letter IATA airport or airline code assigned to the entity.
-
E.
hasAirportCodeRegion
Indicates that an airport code is associated with, or belongs to, a specific geographic or administrative region.
- 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_69b345158c748190a2c040fce2da9980 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b3548b1ca08190b3136867c7098d86 |
completed | March 13, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69b34f5b36a881909bf2e970aa523390 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:28 p.m.