Triple
T24284598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 4 × 100 metres relay |
E605635
|
entity |
| Predicate | firstLegSegment |
P40286
|
FINISHED |
| Object | run on curve |
—
|
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: run on curve | Statement: [4 × 100 metres relay, firstLegSegment, run on curve]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstLegSegment Context triple: [4 × 100 metres relay, firstLegSegment, run on curve]
-
A.
firstLeg
chosen
Indicates that one entity represents the initial segment or starting portion of a multi-part journey, sequence, or process involving another entity.
-
B.
secondLegOrigin
Indicates the location from which the second leg of a multi-leg journey or route begins.
-
C.
originalLegFinish
Indicates that an entity represents the final segment or completion state of an original leg in a multi-leg process or journey.
-
D.
legOrder
Indicates the sequential position or ordering of a specific leg within a multi-leg structure, process, or route.
-
E.
legs
Indicates that an entity possesses legs, specifying the presence or number of leg-like appendages associated with it.
- 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f54c5948190a28207d47d6205e4 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:08 a.m.