Triple
T33951386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | women's 100 metres hurdles |
E870449
|
entity |
| Predicate | distanceBetweenHurdles |
P205256
|
FINISHED |
| Object | 8.5 metres |
—
|
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: 8.5 metres | Statement: [women's 100 metres hurdles, distanceBetweenHurdles, 8.5 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceBetweenHurdles Context triple: [women's 100 metres hurdles, distanceBetweenHurdles, 8.5 metres]
-
A.
numberOfHurdles
Indicates the quantity of hurdles involved in or associated with a particular event, activity, or entity.
-
B.
distancePerRace
Indicates the total distance covered in a single race event or instance.
-
C.
hopDistance
Indicates the number of intermediate steps or "hops" required to traverse from one entity to another within a network or graph.
-
D.
raceDistanceType
Indicates the specific type or category of distance over which a race is conducted.
-
E.
distancePerLeg
Indicates the distance covered in a single leg or segment of a multi-part journey or route.
- F. None of above. chosen
Provenance (4 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_69f3499c2d7481909c953a5010227725 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:49 a.m.