Triple
T30605755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porto Corsa |
E779037
|
entity |
| Predicate | raceCircuitCharacteristic |
P150670
|
FINISHED |
| Object | tight street sections |
—
|
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: tight street sections | Statement: [Porto Corsa, raceCircuitCharacteristic, tight street sections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: raceCircuitCharacteristic Context triple: [Porto Corsa, raceCircuitCharacteristic, tight street sections]
-
A.
raceCircuitName
Indicates the name assigned to a specific race circuit within a racing context.
-
B.
hasStreetCircuitCharacteristics
chosen
Indicates that something possesses qualities or features typical of a street circuit, such as being laid out on public roads and having characteristics associated with that type of racing venue.
-
C.
raceWinCircuit
Indicates that an entity wins a race that takes place on a specific circuit.
-
D.
raceComponent
Indicates that one entity is a constituent part, segment, or stage within a larger race or racing event involving another entity.
-
E.
typicalTrackCharacteristics
Indicates that the associated characteristics represent the usual or standard features of a given track.
- 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_69f224a21fc08190abd9d8dd9eb6bb4c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f697eabb048190bc01a830f14942c6 |
completed | May 3, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 8:25 p.m.