Triple
T27650071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sendagaya area |
E696825
|
entity |
| Predicate | hasRailLineAccess |
P57688
|
FINISHED |
| Object | JR Chuo-Sobu Line |
—
|
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: JR Chuo-Sobu Line | Statement: [Sendagaya area, hasRailLineAccess, JR Chuo-Sobu Line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailLineAccess Context triple: [Sendagaya area, hasRailLineAccess, JR Chuo-Sobu Line]
-
A.
hasRailOrRoadAccess
Indicates that an entity is connected to or reachable by either a railway network, a road network, or both.
-
B.
hasRail
Indicates that something is equipped with, includes, or is connected to a rail or rail system.
-
C.
hasRailRoute
Indicates that there exists a rail-based transportation route or connection between the related entities.
-
D.
railAccessModel
Indicates the type or pattern of how rail infrastructure or services are accessed or connected between locations or entities.
-
E.
railwayAccess
chosen
Indicates that an entity has direct access to, connection with, or service by a railway line or station.
- 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_69ef590abd3c8190834d0193bde12007 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 27, 2026, 2:31 p.m.