Triple
T6433689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Metro 10000 series |
E129838
|
entity |
| Predicate | hasLEDHeadlights |
P59557
|
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: [Tokyo Metro 10000 series, hasLEDHeadlights, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLEDHeadlights Context triple: [Tokyo Metro 10000 series, hasLEDHeadlights, yes]
-
A.
headlightType
chosen
Indicates the specific kind or category of headlights that an entity is equipped with or uses.
-
B.
hasOnboardLEDs
Indicates that one entity is equipped with built-in LED lights as part of its hardware.
-
C.
hasNumberOfMainLights
Indicates the relationship that specifies how many primary or main lights are associated with an entity.
-
D.
hasOnboardLED
Indicates that an entity includes an LED that is physically integrated into its hardware.
-
E.
hasVehicleFeature
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
- 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_69c0084caac48190a7bc2ad8ba44536f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0693f73ec8190883470b57f8141aa |
completed | March 22, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69c060f96980819091bab9335922a457 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:45 p.m.