Triple
T7041374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herrero |
E163519
|
entity |
| Predicate | isRelatedTo |
P37
|
FINISHED |
| Object | Herrera |
E185510
|
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: Herrera | Statement: [Herrero, isRelatedTo, Herrera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Herrera Context triple: [Herrero, isRelatedTo, Herrera]
-
A.
Herrera
chosen
Herrera is a common Spanish surname borne by numerous notable figures across sports, politics, arts, and other fields in the Spanish-speaking world.
-
B.
Herrero
Herrero is a Spanish occupational surname derived from the word for "blacksmith" or "smith."
-
C.
Esquivel
Esquivel is a Spanish-language surname borne by various notable figures in literature, politics, and the arts across Latin America.
-
D.
Velasco
Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
-
E.
Balderas
Balderas is a major Mexico City Metro station known for its central location and high passenger traffic.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e22544708190b0dffb5256d4cda6 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7886a24c48190bb461f26f87d6ef8 |
completed | March 28, 2026, 7:51 a.m. |
Created at: March 27, 2026, 2:36 p.m.