Triple
T5516834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PUB |
E144704
|
entity |
| Predicate | appliesToTransportFacilityType |
P65202
|
FINISHED |
| Object | airport |
—
|
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: airport | Statement: [PUB, appliesToTransportFacilityType, airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToTransportFacilityType Context triple: [PUB, appliesToTransportFacilityType, airport]
-
A.
appliesToTransportMode
Indicates that a rule, condition, or characteristic is specifically associated with and relevant to a particular mode of transport.
-
B.
appliesToTransitSystem
Indicates that something (such as a rule, policy, feature, or condition) is relevant or applicable to a particular transit or transportation system.
-
C.
transportationFacility
Indicates that one entity is a facility or location used for the transportation or transit of people or goods in relation to another entity.
-
D.
hasRailFacility
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
-
E.
appliesToTransitLine
Indicates that a rule, condition, or characteristic is specifically associated with and relevant to a particular transit line.
- F. None of above. chosen
Provenance (4 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_69c008f77ff88190b0cd50ca207295d1 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f5e8ce08190b7f5f2131bebcd4f |
completed | March 22, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69c01b0a06348190b39ac9fe80d2836a |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f051e508190b3886d87b4afdd0b |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:33 p.m.