Triple
T25745877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexus F |
E648342
|
entity |
| Predicate | distinctionFromFSPORT |
P159499
|
FINISHED |
| Object | F models are full high-performance vehicles |
—
|
NE NERFINISHED |
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: F models are full high-performance vehicles | Statement: [Lexus F, distinctionFromFSPORT, F models are full high-performance vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distinctionFromFSPORT Context triple: [Lexus F, distinctionFromFSPORT, F models are full high-performance vehicles]
-
A.
relatedSport
Indicates that there is an association or connection between an entity and a particular sport.
-
B.
favoriteSport
Indicates that one entity has a particular sport that it prefers above all others.
-
C.
alsoUsedForSport
Indicates that something primarily associated with one purpose is additionally used for sporting activities or athletic purposes.
-
D.
partOfSports
Indicates that one entity is a component, segment, or element within a larger sports-related activity, event, or organization.
-
E.
primarySports
Indicates that a particular sport is the main or most important sport associated with an entity (such as a person, team, or organization).
- 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_69e7ab306eec8190b05c312c6ab186b8 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fd1e9dd081908c70074c8aa49e51 |
completed | May 2, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69f4a0fed15881909b789251fe5d8d45 |
completed | May 1, 2026, 12:47 p.m. |
| PDg | Predicate description generation | batch_69f55e497fa081909bc59a7b92c5df59 |
completed | May 2, 2026, 2:15 a.m. |
Created at: April 22, 2026, 3:51 a.m.