Triple
T13288580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dipper |
E316504
|
entity |
| Predicate | relativePositionOnCircuit |
P20526
|
FINISHED |
| Object | after Skyline |
—
|
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: after Skyline | Statement: [The Dipper, relativePositionOnCircuit, after Skyline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativePositionOnCircuit Context triple: [The Dipper, relativePositionOnCircuit, after Skyline]
-
A.
relativePositionOnCourse
chosen
Indicates the positional relationship of one participant or object relative to another along a defined course or route.
-
B.
positionOnRace
Indicates the relative ranking or placement an entity holds within the context of a race or competitive event.
-
C.
relativePositionInStadium
Indicates the spatial relationship between entities based on where they are located relative to each other within a stadium.
-
D.
positionInRound
Indicates the specific ordinal place an entity occupies within a given round or sequence of rounds.
-
E.
positionInPark
Indicates that one entity occupies a specific location or spot within a park.
- 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6535688190a5a4549b7be2d611 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:27 p.m.