Triple
T7982998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joan Gamper |
E185618
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Juan Gamper |
E185618
|
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: Juan Gamper | Statement: [Joan Gamper, alsoKnownAs, Juan Gamper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Juan Gamper Context triple: [Joan Gamper, alsoKnownAs, Juan Gamper]
-
A.
Joan Gamper
chosen
Joan Gamper was a Swiss football pioneer and sports executive best known as the founder and early driving force behind FC Barcelona.
-
B.
Luigi Bianchi
Luigi Bianchi was an Italian mathematician known for his influential work in differential geometry and the theory of Riemannian manifolds.
-
C.
Luigi Bianchi
Luigi Bianchi was an Italian figure notable for founding the Vatican City’s official newspaper, L'Osservatore Romano.
-
D.
Jules Rimet
Jules Rimet was a French football administrator best known as the long-serving FIFA president who founded the FIFA World Cup tournament.
-
E.
Elie Delaunay
Elie Delaunay was a 19th-century French painter known for his refined academic style and historical and mythological subjects.
- 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_69ca829a2cfc819083d591d58ec04075 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c2a1aa881909c3cea280dff38f5 |
completed | March 31, 2026, 3:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63b96ed48190b752865ef3855e46 |
completed | April 1, 2026, 12:15 a.m. |
Created at: March 30, 2026, 5:15 p.m.