Triple
T11996460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guillermo Arriaga |
E285542
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Guillermo |
E11442
|
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: Guillermo | Statement: [Guillermo Arriaga, givenName, Guillermo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guillermo Context triple: [Guillermo Arriaga, givenName, Guillermo]
-
A.
Guillermo
chosen
Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
-
B.
Vicente
Vicente is a given name, common in Spanish- and Portuguese-speaking countries, that corresponds to the English name Vincent.
-
C.
Enrique
Enrique is a Spanish given name equivalent to the English name Henry.
-
D.
Basilio
Basilio is the King of Poland in Calderón de la Barca’s play "La vida es sueño," whose fatalistic decisions about his son’s destiny drive the central conflict of the drama.
-
E.
Basilio
Basilio is the surname of Enriqueta Basilio, the Mexican track and field athlete famed for being the first woman to light the Olympic cauldron at the 1968 Summer Olympics.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c172788190b92042e9d10a48bf |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f640b9a481908de1b7858e3db52c |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:46 p.m.