Triple
T4033071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vicente Blasco Ibáñez |
E83759
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Vicente |
E115514
|
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: Vicente | Statement: [Vicente Blasco Ibáñez, givenName, Vicente]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vicente Context triple: [Vicente Blasco Ibáñez, givenName, Vicente]
-
A.
Vicente
chosen
Vicente is a given name, common in Spanish- and Portuguese-speaking countries, that corresponds to the English name Vincent.
-
B.
Ramón
Ramón is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
C.
Ignacio
Ignacio is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
D.
Eduardo
Eduardo is a masculine given name commonly used in Spanish and Portuguese-speaking countries, equivalent to the English name Edward.
-
E.
Guillermo
Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
- 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_69aed92e29ac819080f7a98b594fec05 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb108fc0819080c8f41da2e558e0 |
completed | March 9, 2026, 4:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5db6b01e48190a2e02597347f3348 |
completed | March 14, 2026, 10:04 p.m. |
Created at: March 9, 2026, 3:36 p.m.