Triple
T672747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Athletics Platinum Label road race |
E13007
|
entity |
| Predicate | eligibleEventType |
P14526
|
FINISHED |
| Object | mass-participation road race with elite field |
—
|
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: mass-participation road race with elite field | Statement: [World Athletics Platinum Label road race, eligibleEventType, mass-participation road race with elite field]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eligibleEventType Context triple: [World Athletics Platinum Label road race, eligibleEventType, mass-participation road race with elite field]
-
A.
typicalEvent
Indicates that the associated event is a common, characteristic, or prototypical occurrence for the given entity or situation.
-
B.
typeOfEvent
Indicates that one entity is classified as a specific kind or category of event.
-
C.
typeOfEventForStart
Indicates the specific kind or category of event that marks the beginning of something.
-
D.
hasEventType
chosen
Indicates that an event is associated with, or classified under, a specific type or category of event.
-
E.
sportEventType
Indicates the specific kind or category of sport associated with a given sporting event.
- 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_69a4933d3bf88190972041cd8cf143b9 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a1b3682c8190a9b9a454480c3446 |
completed | March 1, 2026, 8:29 p.m. |
| PD | Predicate disambiguation | batch_69a49d1a16c48190af89e3b078a4957e |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.