Triple
T18900389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Israel national football team |
E462322
|
entity |
| Predicate | olympicFootballBestResultYear |
P71869
|
FINISHED |
| Object | 1976 Summer Olympics |
—
|
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: 1976 Summer Olympics | Statement: [Israel national football team, olympicFootballBestResultYear, 1976 Summer Olympics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: olympicFootballBestResultYear Context triple: [Israel national football team, olympicFootballBestResultYear, 1976 Summer Olympics]
-
A.
bestOlympicGamesResultYear
chosen
Indicates the year in which an entity achieved its best result at the Olympic Games.
-
B.
wonOlympicFootballTournament
Indicates that an entity secured first place in the Olympic football (soccer) tournament in a given edition of the Olympic Games.
-
C.
bestWorldCupResultYear
Indicates the year in which an entity achieved its best (highest) result in a World Cup tournament.
-
D.
olympicFootballAppearances
Indicates the number of times an entity has participated in Olympic football (soccer) tournaments.
-
E.
olympicBestResult
Indicates the best performance or highest achievement an entity has attained in Olympic competition.
- 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c5289ba48190a6825c4db2e5e48d |
completed | April 20, 2026, 6:18 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e27e1481908a8da10b28f07875 |
completed | April 19, 2026, 9:39 a.m. |
Created at: April 10, 2026, 11:58 a.m.