Triple
T29356136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naha–Tokyo Haneda |
E744447
|
entity |
| Predicate | destinationAirportLocation |
P167959
|
FINISHED |
| Object | Ōta, Tokyo |
—
|
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: Ōta, Tokyo | Statement: [Naha–Tokyo Haneda, destinationAirportLocation, Ōta, Tokyo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: destinationAirportLocation Context triple: [Naha–Tokyo Haneda, destinationAirportLocation, Ōta, Tokyo]
-
A.
destinationAirportName
Indicates the name of the airport that serves as the destination in a travel or flight-related relationship.
-
B.
destinationAirportICAO
Indicates the airport, identified by its ICAO code, that serves as the destination in a flight or travel-related context.
-
C.
destinationAirportInvestigated
Indicates that an airport serving as a destination has been examined or analyzed, typically as part of an investigation or assessment process.
-
D.
destinationAirportRole
Indicates the role an airport plays as the destination point within a given travel, flight, or route relationship.
-
E.
destinationAirportCity2
Indicates the city of the airport that serves as the second (or alternative) destination in a travel or flight-related context.
- 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_69f0a79aee588190b490f19d93c6e52d |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66e5f7e30819094530abceabd5f43 |
completed | May 2, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66d75a8788190aa9ca2c977429045 |
completed | May 2, 2026, 9:32 p.m. |
Created at: April 28, 2026, 2:12 p.m.