Triple
T20172942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1996 Stock |
E492012
|
entity |
| Predicate | hasTrailerCar |
P138962
|
FINISHED |
| Object | T |
—
|
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: T | Statement: [1996 Stock, hasTrailerCar, T]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrailerCar Context triple: [1996 Stock, hasTrailerCar, T]
-
A.
hasSeparateTrailingTruck
Indicates that an entity is accompanied by a distinct, independently attached trailing truck or carriage rather than having it integrated into its main structure.
-
B.
hasTrunk
Indicates that one entity possesses or is equipped with a trunk as a physical feature or component.
-
C.
trailerField
Indicates that one entity is a field or attribute specifically associated with a trailer (such as a trailer record, object, or data structure).
-
D.
hasSeparateLeadingTruck
Indicates that an object or vehicle is accompanied by a distinct, independently operated leading truck unit.
-
E.
towingCapability
Indicates the maximum load or object weight that one entity is able to pull or tow.
- F. None of above. chosen
Provenance (4 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66849709c81909b65b421282f9f3b |
completed | April 20, 2026, 5:54 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56700b1a08190ace53cf95827d72d |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:35 p.m.