Triple
T12604196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vicenç Ferrer |
E300933
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Ferrer |
E636597
|
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: Ferrer | Statement: [Vicenç Ferrer, familyName, Ferrer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ferrer Context triple: [Vicenç Ferrer, familyName, Ferrer]
-
A.
Ferrer
chosen
Ferrer is a Spanish-origin surname borne by numerous notable figures in the arts, sports, and public life.
-
B.
Rafel Nadal i Farreras
Rafel Nadal i Farreras is a Spanish journalist and writer from Mallorca, known for his work in newspapers and his award-winning novels and memoirs.
-
C.
Fernando Lopez
Fernando Lopez was a Filipino politician and businessman who served multiple terms as Vice President of the Philippines in the mid-20th century.
-
D.
Félix Cuevas
Félix Cuevas is a bus rapid transit station on Mexico City’s Metrobús system, serving passengers along one of the city’s main north–south corridors.
-
E.
Feliciano
Feliciano is a given name of Latin origin, commonly used in Romance-language countries and related to the name Felix.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e6e20481908bca684c4b497c48 |
completed | April 10, 2026, 7:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ecb09e481909d688f174372dde7 |
completed | May 2, 2026, 8:30 p.m. |
Created at: April 9, 2026, 5:10 p.m.