Triple
T6637726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France women’s national football team |
E150499
|
entity |
| Predicate | bestOlympicGamesResult |
P33011
|
FINISHED |
| Object | fourth place |
—
|
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: fourth place | Statement: [France women’s national football team, bestOlympicGamesResult, fourth place]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestOlympicGamesResult Context triple: [France women’s national football team, bestOlympicGamesResult, fourth place]
-
A.
olympicBestResult
chosen
Indicates the best performance or highest achievement an entity has attained in Olympic competition.
-
B.
olympicGoldMedals
Indicates that an entity has won one or more Olympic gold medals.
-
C.
olympicGames
Indicates that an entity is an edition or instance of the Olympic Games event.
-
D.
OlympicGoldMedalSport
Indicates that the subject sport is one in which the object athlete or team has won an Olympic gold medal.
-
E.
olympicGoldMedalInEvent
Indicates that an entity has won an Olympic gold medal in a specified 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_69c687f0ceb08190bf40807bfc605fa5 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c308a08881908501c862b3029321 |
completed | March 27, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c6ad024860819084b9b535b136ede6 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:59 p.m.