Triple
T295927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guillermo del Toro |
E6092
|
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 del Toro, givenName, Guillermo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guillermo Context triple: [Guillermo del Toro, givenName, Guillermo]
-
A.
Guillermo
chosen
Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
-
B.
Eduardo
Eduardo is a masculine given name commonly used in Spanish and Portuguese-speaking countries, equivalent to the English name Edward.
-
C.
José
José is the given first name of Major League Baseball manager and former player Alex Cora.
-
D.
Andrés
Andrés is a Spanish given name commonly used as the equivalent of Andrew.
-
E.
Pedro
Pedro is the Spanish and Portuguese given name equivalent to the English name Peter and the French name Pierre.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2e979663481908cf9622e59fed041 |
completed | Feb. 28, 2026, 1:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3c4141d288190a6873cf20e360fe1 |
completed | March 1, 2026, 4:44 a.m. |
Created at: Feb. 28, 2026, 1:06 p.m.