Triple
T33723421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renaud Lavillenie |
E864078
|
entity |
| Predicate | worldRecordVenue |
P106777
|
FINISHED |
| Object | Donetsk |
—
|
NE NERFINISHED |
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: Donetsk | Statement: [Renaud Lavillenie, worldRecordVenue, Donetsk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldRecordVenue Context triple: [Renaud Lavillenie, worldRecordVenue, Donetsk]
-
A.
largestVenueOf
Indicates that one venue is the largest (typically by capacity, area, or scale) among a specified set or within a particular context.
-
B.
worldRecordEvent
Indicates that an event involves the setting, holding, or recognition of a world record.
-
C.
largestEvent
Indicates that the referenced event is the one with the greatest magnitude, size, or extent among a specified set of events.
-
D.
worldSpeedRecordLocation
Indicates the location where a world speed record was achieved or officially recorded.
-
E.
significantVenueFor
chosen
Indicates that a venue plays an important or notable role in relation to a particular entity, event, or activity.
- 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_69f34989871c81908682e22a2fe4b829 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: May 1, 2026, 1:44 a.m.