Triple
T29430449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Villalobos Vélez |
E746413
|
entity |
| Predicate | followsSpanishNamingCustom |
P66703
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Villalobos Vélez, followsSpanishNamingCustom, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsSpanishNamingCustom Context triple: [Villalobos Vélez, followsSpanishNamingCustom, true]
-
A.
followsIberianNamingCustom
chosen
Indicates that a person’s full name is structured according to Iberian naming customs, typically including given names followed by multiple family surnames in a culturally specific order.
-
B.
isEquivalentSurnameInSpanish
Indicates that two surnames are considered equivalent when translated to or used in Spanish, even if their spellings or forms differ.
-
C.
hasNameInSpanish
Indicates that an entity is associated with a specific name expressed in the Spanish language.
-
D.
usesGentilicFor
Indicates that one entity refers to another using a gentilic (a demonym or term denoting origin, nationality, or regional affiliation).
-
E.
fractionalNameInSpanish
Indicates that an entity’s fractional value is expressed or named in the Spanish language.
- F. None of above.
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_69f0a7a06e0081908add494075912eb4 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: April 28, 2026, 3:12 p.m.