Triple
T38220756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kintetsu Namba Line at Osaka-Namba Station |
E1012001
|
entity |
| Predicate | hasLineName |
P28725
|
FINISHED |
| Object | Kintetsu Namba 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: Kintetsu Namba Line | Statement: [Kintetsu Namba Line at Osaka-Namba Station, hasLineName, Kintetsu Namba Line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLineName Context triple: [Kintetsu Namba Line at Osaka-Namba Station, hasLineName, Kintetsu Namba Line]
-
A.
lineName
chosen
Indicates the specific name or designation assigned to a particular line (such as a route, path, or service) that distinguishes it from other lines.
-
B.
hasNinthLineName
Indicates that an entity is associated with a specific name used as its ninth line or label in an ordered sequence.
-
C.
hasLineageName
Indicates that an entity is associated with or identified by a specific lineage name within a genealogical or hierarchical context.
-
D.
hasLRTLine
Indicates that a location, station, or area is served by or lies along a specific light rail transit (LRT) line.
-
E.
formerLineName
Indicates that the object is a previous or former name by which the referenced line was known.
- 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_69f76dd25e0c81909f2abd0803e5e3ee |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff255b84788190a94682f4efe1d0b8 |
completed | May 9, 2026, 12:15 p.m. |
| PD | Predicate disambiguation | batch_69ff24f3ab108190bb017a656cff3d82 |
completed | May 9, 2026, 12:13 p.m. |
Created at: May 3, 2026, 4:30 p.m.