Triple
T9282517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Côte d'Ivoire national football team |
E223102
|
entity |
| Predicate | regionalTournamentAppearances |
P25988
|
FINISHED |
| Object | many |
—
|
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: many | Statement: [Côte d'Ivoire national football team, regionalTournamentAppearances, many]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalTournamentAppearances Context triple: [Côte d'Ivoire national football team, regionalTournamentAppearances, many]
-
A.
regionalCupAppearances
chosen
Indicates the number of times an entity has participated in a specified regional cup competition.
-
B.
WorldChampionshipAppearances
Indicates the number of times an entity has participated in a world championship competition.
-
C.
playedInTournament
Indicates that an entity participated as a competitor or player in a specific tournament.
-
D.
scoredInTournament
Indicates that an entity achieved a score or points during a particular tournament.
-
E.
hasTournament
Indicates that an entity organizes, hosts, or is associated with a specific tournament.
- 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_69ca842123588190b3f2e1a69037d141 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd081d60a88190b49b040d0e7415bf |
completed | April 1, 2026, 11:57 a.m. |
| PD | Predicate disambiguation | batch_69cc7a576ec88190bbb787eb82e2e539 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:34 p.m.