Triple
T12632843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinjuku Marui |
E301685
|
entity |
| Predicate | locatedInTransportArea |
P106124
|
FINISHED |
| Object | Shinjuku Station area |
—
|
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: Shinjuku Station area | Statement: [Shinjuku Marui, locatedInTransportArea, Shinjuku Station area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInTransportArea Context triple: [Shinjuku Marui, locatedInTransportArea, Shinjuku Station area]
-
A.
locatedInTransportCorridor
Indicates that an entity is situated within a designated transport corridor used for the movement of people or goods.
-
B.
hasBoardingAreaFor
Indicates that one entity provides or contains a designated area where passengers can board another entity (such as a vehicle or vessel).
-
C.
isInTransportNetwork
Indicates that an entity is part of, connected to, or contained within a specific transport network or system.
-
D.
partlyInAdministrativeArea
Indicates that an entity is located such that only a portion of it lies within a specified administrative area (e.g., a city, county, or region).
-
E.
seatOftenLocatedIn
Indicates that one type of seat is commonly or typically found within a particular location or setting.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960b47130819097e1162ed4fc993a |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d961acadb8819098de743bc951fedb |
completed | April 10, 2026, 8:46 p.m. |
Created at: April 9, 2026, 5:15 p.m.