Triple
T36756395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Escort RS Cosworth |
E908062
|
entity |
| Predicate | tuningPartner |
P71560
|
FINISHED |
| Object | Cosworth |
—
|
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: Cosworth | Statement: [Ford Escort RS Cosworth, tuningPartner, Cosworth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tuningPartner Context triple: [Ford Escort RS Cosworth, tuningPartner, Cosworth]
-
A.
tunedBy
chosen
Indicates that one entity has been adjusted or calibrated in its settings, parameters, or configuration by another entity.
-
B.
tuningScope
Indicates the specific aspect, component, or range of a system that is being adjusted or optimized through a tuning action.
-
C.
tuningType
Indicates the specific method or configuration by which something is adjusted or calibrated to achieve a desired performance or behavior.
-
D.
tuning
Indicates the adjustment or calibration of something’s parameters or settings to achieve desired performance or behavior.
-
E.
tuningRange
Indicates the range of values over which something can be tuned or adjusted.
- 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_69f76e779bec8190be0e1f87a131e0f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.