Triple
T38358799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crowthorne |
E1046409
|
entity |
| Predicate | roleOnCircuit |
P165140
|
FINISHED |
| Object | first major braking point |
—
|
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: first major braking point | Statement: [Crowthorne, roleOnCircuit, first major braking point]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOnCircuit Context triple: [Crowthorne, roleOnCircuit, first major braking point]
-
A.
roleOn
chosen
Indicates that an entity holds or performs a specific role or function within another entity, context, or activity.
-
B.
roleOnLine1
Indicates that an entity holds a specific role or function associated with the first line of a multi-line structure or sequence.
-
C.
roleInOperation
Indicates that an entity holds a specific function, duty, or position within a particular operation or activity.
-
D.
roleInLap
Indicates the specific function or position an entity holds during a particular lap within a sequence of laps.
-
E.
roleInMCU
Indicates that one entity portrays or has a specific character role within the Marvel Cinematic Universe in relation to the other entity.
- 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_69f76e3a94fc81908edc175e8d259e80 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: May 3, 2026, 4:31 p.m.