Triple
T15256738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osaka Metro 23 series |
E364664
|
entity |
| Predicate | hasMultipleUnitsControl |
P66171
|
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: [Osaka Metro 23 series, hasMultipleUnitsControl, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleUnitsControl Context triple: [Osaka Metro 23 series, hasMultipleUnitsControl, yes]
-
A.
hasMultipleUnitControl
chosen
Indicates that a single controller or agent is able to direct, manage, or operate more than one unit simultaneously.
-
B.
multipleUnit
Indicates that an entity is composed of or associated with more than one unit of the same type.
-
C.
hasMultiple
Indicates that an entity is associated with more than one instance or occurrence of another related entity.
-
D.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
E.
hasSubunits
Indicates that an entity is composed of or organized into smaller constituent units that are part of its structure.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084b97908190b3bf7ea7bd75bdc0 |
completed | April 15, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69deca8d1bd48190a4b94f29b425e335 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:13 a.m.