Triple
T13844631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leo Encinas Cruz |
E332763
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Encinas Cruz |
E923789
|
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: Encinas Cruz | Statement: [Leo Encinas Cruz, familyName, Encinas Cruz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Encinas Cruz Context triple: [Leo Encinas Cruz, familyName, Encinas Cruz]
-
A.
Encinas Cruz
chosen
Encinas Cruz is the compound Spanish surname shared by actress Penélope Cruz and Javier Bardem’s daughter, Luna.
-
B.
Autlán de Navarro
Autlán de Navarro is a municipality and city in the Mexican state of Jalisco, known for its agricultural economy and traditional cultural festivities.
-
C.
Carrillo
Carrillo is a Spanish-origin surname borne by numerous notable individuals across the Spanish-speaking world and beyond.
-
D.
Garces
Garces is a Spanish-origin surname borne by various notable individuals across fields such as entertainment, sports, and public service.
-
E.
Velasco
Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02b1a25c8190a9f85ba43c421188 |
completed | April 14, 2026, 9:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c70816e48190949b16ae6e744d22 |
completed | May 3, 2026, 10:07 p.m. |
Created at: April 9, 2026, 10:13 p.m.