Triple
T2201452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ignacio Zaragoza |
E50497
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ignacio |
E114337
|
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: Ignacio | Statement: [Ignacio Zaragoza, givenName, Ignacio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ignacio Context triple: [Ignacio Zaragoza, givenName, Ignacio]
-
A.
Ignacio
chosen
Ignacio is a masculine given name of Spanish origin 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.
Pascual
Pascual is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
D.
Martín
Martín is a masculine given name of Latin origin, commonly used in Spanish-speaking countries and derived from the name Martinus, associated with the Roman god Mars.
-
E.
Alejo
Alejo is a Spanish given name commonly used as a short form of Alejandro.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfa1b41c8190b0f7467d0dcdfbcd |
completed | March 7, 2026, 6:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc01a30608190839f9e11db0f7def |
completed | March 10, 2026, 6:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.