Triple
T27464284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mulsanne Straight |
E693133
|
entity |
| Predicate | chicanesAddedIn |
P162416
|
FINISHED |
| Object | 1990 |
—
|
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: 1990 | Statement: [Mulsanne Straight, chicanesAddedIn, 1990]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chicanesAddedIn Context triple: [Mulsanne Straight, chicanesAddedIn, 1990]
-
A.
hasChicane
Indicates that one entity incorporates or features a chicane (a sharp, S-shaped bend or series of bends), typically in the context of a track, route, or path.
-
B.
keyChicane
Indicates a relationship where something functions as a primary or defining chicane (a key turning or zigzag feature) within a larger structure, path, or system.
-
C.
chasesAcross
Indicates that one entity actively pursues another entity while moving from one side or area to another across some intervening space or surface.
-
D.
hasPitLane
Indicates that a racing circuit, track, or similar facility includes a designated pit lane area for vehicle servicing and related activities.
-
E.
CARTChampionships
Indicates the number of CART (Championship Auto Racing Teams) series championships an entity has won.
- 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_69ef538105548190a771cc5a0cf8c211 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f62dfbe6508190a6871084c5afe20f |
completed | May 2, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69f623aaf40081909f947431424a1d55 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f624c006788190a2f4d5015c96463f |
completed | May 2, 2026, 4:22 p.m. |
Created at: April 27, 2026, 12:51 p.m.