Triple
T12183578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plaza Sésamo |
E290277
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Pancho |
E310383
|
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: Pancho | Statement: [Plaza Sésamo, hasCharacter, Pancho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pancho Context triple: [Plaza Sésamo, hasCharacter, Pancho]
-
A.
Pancho
chosen
Pancho is a common Spanish nickname typically used as a familiar or affectionate form of the given name Francisco.
-
B.
Poncho Ramirez
Poncho Ramirez is a character from the Predator franchise, typically depicted as a skilled and battle-hardened member of an elite military team.
-
C.
Pancho Gonzales
Pancho Gonzales was a dominant American tennis player of the 1940s–1960s, renowned for his powerful serve-and-volley game and long reign as one of the world’s top professionals.
-
D.
Don Criqui
Don Criqui is an American sportscaster best known for his long-running play-by-play work on NFL broadcasts and other major sporting events.
-
E.
Lalo
Lalo is a common Spanish nickname for the given name Eduardo.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d915fd8dac8190928059ad2b6bbbf3 |
completed | April 10, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6aecb0881909084f3ff2a9e52ea |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:50 p.m.