Triple
T33723429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renaud Lavillenie |
E864078
|
entity |
| Predicate | olympicSilverCity |
P180576
|
FINISHED |
| Object | Rio de Janeiro |
—
|
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: Rio de Janeiro | Statement: [Renaud Lavillenie, olympicSilverCity, Rio de Janeiro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: olympicSilverCity Context triple: [Renaud Lavillenie, olympicSilverCity, Rio de Janeiro]
-
A.
OlympicGoldMedalCity
Indicates that a city is the location where an Olympic Games took place in which a gold medal was awarded.
-
B.
olympicBronzeMedalCity
Indicates that a city is the location where an Olympic bronze medal was won or awarded.
-
C.
olympicSilverMedals
Indicates that the subject has won one or more silver medals at the Olympic Games.
-
D.
OlympicSilverInEvent
Indicates that an entity won a silver medal in a specified Olympic event.
-
E.
lastOlympicCity
Indicates the relationship where a city is identified as the most recent host of the Olympic Games for a given edition or context.
- 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_69f34989871c81908682e22a2fe4b829 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: May 1, 2026, 1:44 a.m.