Triple
T32382753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yaesu exit of Tokyo Station |
E827465
|
entity |
| Predicate | hasSubExit |
P48913
|
FINISHED |
| Object | Yaesu North Exit |
—
|
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: Yaesu North Exit | Statement: [Yaesu exit of Tokyo Station, hasSubExit, Yaesu North Exit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubExit Context triple: [Yaesu exit of Tokyo Station, hasSubExit, Yaesu North Exit]
-
A.
hasExitFor
Indicates that something provides or includes a specific exit intended for a particular destination, purpose, or user.
-
B.
hasNumberOfExits
Indicates the relationship that specifies how many exits are associated with a given entity.
-
C.
hasNumberedExit
Indicates that an entity (such as a road or highway) includes or is associated with an exit that has an assigned number.
-
D.
hasExitList
Indicates that an entity is associated with a collection of defined exits or exit points.
-
E.
hasExits
chosen
Indicates that an entity provides one or more ways out or routes leading from it to other locations or states.
- 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_69f349177ddc8190ab0583f05597056b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff0214d7348190904688376df99bce |
completed | May 9, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69feffd62fec8190a855922c8b3c57cf |
completed | May 9, 2026, 9:35 a.m. |
Created at: May 1, 2026, 12:51 a.m.