Triple
T13815106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | women's 3000 metre relay |
E331992
|
entity |
| Predicate | trackLengthStandard |
P18065
|
FINISHED |
| Object | 111.12 metre oval |
—
|
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: 111.12 metre oval | Statement: [women's 3000 metre relay, trackLengthStandard, 111.12 metre oval]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trackLengthStandard Context triple: [women's 3000 metre relay, trackLengthStandard, 111.12 metre oval]
-
A.
typicalTrackLengthRange
Indicates the usual minimum and maximum lengths that a track associated with something tends to fall between.
-
B.
typicalLength
chosen
Indicates the usual or characteristic length associated with an entity or phenomenon.
-
C.
standardRoundLength
Indicates that there is a defined, typical duration assigned to a single round within a process, activity, or game.
-
D.
trailLengthCategory
Indicates the classification of a trail based on its total length (e.g., short, medium, long).
-
E.
trackLengthApproxKm
Indicates that one entity has an approximate track length, measured in kilometers, 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02806e148190996f58934e66d7d8 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc862e9608190bd8a3d883959b7e4 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:12 p.m.