Triple
T1453263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osaka Metro Sennichimae Line |
E31340
|
entity |
| Predicate | hasLineCode |
P19896
|
FINISHED |
| Object | S |
—
|
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: S | Statement: [Osaka Metro Sennichimae Line, hasLineCode, S]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLineCode Context triple: [Osaka Metro Sennichimae Line, hasLineCode, S]
-
A.
usesLineCode
chosen
Indicates that one entity employs or references a specific line code as part of its operation, identification, or communication.
-
B.
hasLineNumber
Indicates that something is associated with a specific line number, typically denoting its position within an ordered sequence such as lines of text or code.
-
C.
hasModelLine
Indicates that an item, product, or entity belongs to or is associated with a particular model line or series.
-
D.
hasProgramCode
Indicates that an entity is associated with a specific program identifier or code used to reference or classify it within a system.
-
E.
isLinedWith
Indicates that one object or surface is covered, edged, or internally coated along its length or area with another material or layer.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c57e82d48190a30a4512f39f5de0 |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47cdbd0819092022344a2f4ad7b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.