Triple
T6765131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toei Asakusa Line Nihonbashi Station |
E154698
|
entity |
| Predicate | isInBusinessArea |
P16988
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Toei Asakusa Line Nihonbashi Station, isInBusinessArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInBusinessArea Context triple: [Toei Asakusa Line Nihonbashi Station, isInBusinessArea, yes]
-
A.
isInBusinessDistrict
chosen
Indicates that an entity is located within a designated business or commercial district area.
-
B.
isInArea
Indicates that one entity is located within the spatial bounds or region defined by another entity.
-
C.
hasKeyBusinessArea
Indicates that an entity is associated with or operates within a particular primary business area or domain.
-
D.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
E.
operatesWithin
Indicates that one entity carries out its activities, functions, or operations inside the scope, boundaries, or jurisdiction defined by another entity.
- 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_69c688109c1c8190added9a221292af0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d22ed30881909e1bfcfb8cf175a2 |
completed | March 27, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:12 p.m.