Triple
T7803300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlético de Kolkata |
E180483
|
entity |
| Predicate | notablePlayer |
P304
|
FINISHED |
| Object | Luis García |
E583238
|
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: Luis García | Statement: [Atlético de Kolkata, notablePlayer, Luis García]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luis García Context triple: [Atlético de Kolkata, notablePlayer, Luis García]
-
A.
Luis García
chosen
Luis García is a common Spanish name shared by several notable figures, including professional footballers, a baseball player, and other public personalities.
-
B.
Francisco Vela
Francisco Vela was a Guatemalan engineer and cartographer best known for creating the famous three-dimensional Relief Map of Guatemala in Guatemala City.
-
C.
José Gómez
José Gómez was a figure significant enough in Chilean or maritime history that the remote Pacific island Salas y Gómez was named in his honor.
-
D.
Cristo Fernández
Cristo Fernández is a Mexican actor and former professional footballer best known for playing the exuberant footballer Dani Rojas on the television series "Ted Lasso."
-
E.
Javier García
Javier García is a common Spanish name shared by multiple notable individuals across fields such as sports, politics, and the arts.
- 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf635a4648190af907a686d87f073 |
completed | March 30, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc55d5650c8190862d89d1dcc488b4 |
completed | March 31, 2026, 11:16 p.m. |
Created at: March 30, 2026, 4:34 p.m.