Triple
T36075482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Grand Prix |
E1043483
|
entity |
| Predicate | previousMainStraightName |
P184552
|
FINISHED |
| Object | International Pits Straight |
—
|
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: International Pits Straight | Statement: [British Grand Prix, previousMainStraightName, International Pits Straight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousMainStraightName Context triple: [British Grand Prix, previousMainStraightName, International Pits Straight]
-
A.
previousStreetName
Indicates that one street name was formerly used for a street that now has a different, current name.
-
B.
mainStraightName
chosen
Indicates the name assigned to the primary straight segment or main straight portion of something (such as a route, track, or road).
-
C.
hasFormerStreetName
Indicates that an entity (such as a street or place) was previously known by a different street name.
-
D.
formerLineName
Indicates that the object is a previous or former name by which the referenced line was known.
-
E.
previousLocationName
Indicates that one entity specifies the name of a location where another entity was situated or occurred before its current location.
- 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_69f76e2fd3248190b900d9a492bf5a7a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff84df768c81908c65a1a7e33103ad |
completed | May 9, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69ff848d0af881908ee42c27a58af47e |
completed | May 9, 2026, 7:01 p.m. |
Created at: May 3, 2026, 4:08 p.m.