Triple
T12990210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas N'Kono |
E321882
|
entity |
| Predicate | memberOfSportsTeam |
P330
|
FINISHED |
| Object | Bolívar |
E285120
|
NE 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: Bolívar | Statement: [Thomas N'Kono, memberOfSportsTeam, Bolívar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bolívar Context triple: [Thomas N'Kono, memberOfSportsTeam, Bolívar]
-
A.
Bolívar
chosen
Bolívar is a prominent Bolivian football club based in La Paz and one of the most successful teams in the country’s history.
-
B.
Bolívar
Bolívar is a town in northern Peru located within the La Libertad Region, known for its Andean setting and local agricultural activities.
-
C.
Bolivar
Bolivar is Donald Duck’s pet St. Bernard dog in Disney comics, often depicted as a loyal but somewhat lazy companion.
-
D.
Bolivar
Bolivar is a Paris Métro station located in the 19th arrondissement, serving local passengers on the city's urban rail network.
-
E.
Bolivar
Bolivar is a small historic town in Jefferson County, West Virginia, located near Harpers Ferry in the eastern panhandle of the state.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e75b9f88190a54372c2a1223a4e |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8fb70f481908a9a4ca04d6bf93b |
completed | May 3, 2026, 2:54 a.m. |
Created at: April 9, 2026, 8:43 p.m.