Triple
T11467858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 4×100 metre freestyle relay |
E271822
|
entity |
| Predicate | firstLegCharacteristic |
P23297
|
FINISHED |
| Object | must start from a stationary position |
—
|
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: must start from a stationary position | Statement: [4×100 metre freestyle relay, firstLegCharacteristic, must start from a stationary position]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstLegCharacteristic Context triple: [4×100 metre freestyle relay, firstLegCharacteristic, must start from a stationary position]
-
A.
firstLeg
Indicates that one entity represents the initial segment or starting portion of a multi-part journey, sequence, or process involving another entity.
-
B.
legCharacteristic
chosen
Indicates a characteristic, property, or attribute that specifically pertains to the legs of an entity.
-
C.
secondLegOrigin
Indicates the location from which the second leg of a multi-leg journey or route begins.
-
D.
tailCharacteristic
Indicates that an entity possesses a particular property, feature, or quality specifically related to its tail.
-
E.
firstToFeature
Indicates that one entity was the earliest or initial subject to exhibit, include, or present another entity in a given context.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d82949e3688190b024a4980666c94f |
completed | April 9, 2026, 10:33 p.m. |
| PD | Predicate disambiguation | batch_69d8086ecd6c81908f424864857762d6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.