Triple
T18156481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nouvelle Chicane |
E434643
|
entity |
| Predicate | hasTurnCount |
P30551
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Nouvelle Chicane, hasTurnCount, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTurnCount Context triple: [Nouvelle Chicane, hasTurnCount, 2]
-
A.
numberOfTurns
chosen
Indicates the total count of discrete turns or rotations involved in an interaction, process, or motion.
-
B.
hasLeadCountPerSide
Indicates the number of lead elements or units associated with each side in a given context or configuration.
-
C.
hasCountingPeriod
Indicates that there is a defined time span or interval over which occurrences, quantities, or measurements related to an entity are counted or aggregated.
-
D.
hasPlayerCount
Indicates the number of players associated with or participating in a given entity or activity.
-
E.
hasRound
Indicates that an entity possesses, includes, or is associated with a particular round (e.g., a round of an event, game, or process).
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4debe27a88190bd76c6f78fcf1bd1 |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.