Triple
T29356134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naha–Tokyo Haneda |
E744447
|
entity |
| Predicate | locatedInPrefectureOfDestination |
P165597
|
FINISHED |
| Object | Tokyo Metropolis |
—
|
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: Tokyo Metropolis | Statement: [Naha–Tokyo Haneda, locatedInPrefectureOfDestination, Tokyo Metropolis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInPrefectureOfDestination Context triple: [Naha–Tokyo Haneda, locatedInPrefectureOfDestination, Tokyo Metropolis]
-
A.
destinationPrefecture
chosen
Indicates the prefecture that serves as the destination location associated with an entity or event.
-
B.
locatedInRegionOfPrefecture
Indicates that one entity is geographically situated within a specific region that belongs to or is administered as part of a given prefecture.
-
C.
hostPrefecture
Indicates the prefecture that serves as the host location for an event, activity, or entity.
-
D.
locatedInPrefectureLevel
Indicates that one entity is geographically situated within, and administratively belongs to, a specific prefecture-level jurisdiction.
-
E.
locatedInPrefectureLevelCity
Indicates that one entity is geographically situated within the jurisdiction or boundaries of a prefecture-level city.
- 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_69f0a79aee588190b490f19d93c6e52d |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a001cc0ff588190bb7c8a6fd427d02b |
completed | May 10, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_6a001b3ea18c8190aeda7a32b2697490 |
completed | May 10, 2026, 5:44 a.m. |
Created at: April 28, 2026, 2:12 p.m.