Triple
T32448935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suzuka 1000 km (historical) |
E829221
|
entity |
| Predicate | trackCharacteristics |
P179961
|
FINISHED |
| Object | high-speed corners |
—
|
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: high-speed corners | Statement: [Suzuka 1000 km (historical), trackCharacteristics, high-speed corners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trackCharacteristics Context triple: [Suzuka 1000 km (historical), trackCharacteristics, high-speed corners]
-
A.
typicalTrackCharacteristics
Indicates that the associated characteristics represent the usual or standard features of a given track.
-
B.
recordCharacteristic
Indicates that an entity documents or stores a specific characteristic or attribute of another entity.
-
C.
trackCharacter
Indicates that one entity follows, monitors, or keeps a record of another entity’s actions, state, or progression over time.
-
D.
artCharacteristics
Indicates a relationship where specific qualities, styles, or features are attributed to a work of art.
-
E.
ruleCharacteristics
Indicates the defining properties, constraints, or parameters that specify how a particular rule operates or should be applied.
- 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_69f3491d2e5c819092b1c9535beff8ec |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
| PDg | Predicate description generation | batch_69f72920c6208190aa4aba6cb6193109 |
completed | May 3, 2026, 10:53 a.m. |
Created at: May 1, 2026, 12:56 a.m.