Triple
T16180599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honda C70 |
E392672
|
entity |
| Predicate | hasHeadlightShape |
P59557
|
FINISHED |
| Object | rectangular headlight (later models) |
—
|
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: rectangular headlight (later models) | Statement: [Honda C70, hasHeadlightShape, rectangular headlight (later models)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHeadlightShape Context triple: [Honda C70, hasHeadlightShape, rectangular headlight (later models)]
-
A.
headlightType
chosen
Indicates the specific kind or category of headlights that an entity is equipped with or uses.
-
B.
hasLanternShape
Indicates that one entity has the form, outline, or configuration characteristic of a lantern.
-
C.
hasDistinctiveShape
Indicates that an entity possesses a shape or form that is notably different from others and can be easily recognized or distinguished.
-
D.
hasTailShape
Indicates that an entity possesses a tail with a specific shape or form.
-
E.
headShape
Indicates the characteristic form or contour of an entity’s head.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205c92b48190b7125dbbcff3662e |
completed | April 17, 2026, 11:58 a.m. |
| PD | Predicate disambiguation | batch_69e219d642708190ba31a90dce76a210 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.