Triple
T12061622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herman Cornejo |
E287183
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | Erica Cornejo |
E993772
|
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: Erica Cornejo | Statement: [Herman Cornejo, hasRelative, Erica Cornejo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erica Cornejo Context triple: [Herman Cornejo, hasRelative, Erica Cornejo]
-
A.
Erica Cornejo
chosen
Erica Cornejo is an Argentine ballet dancer known for her acclaimed performances as a principal with American Ballet Theatre and later with Boston Ballet.
-
B.
Erica Ortegas
Erica Ortegas is a witty and skilled helmsman of the USS Enterprise in the television series "Star Trek: Strange New Worlds."
-
C.
Andrea Cantillo
Andrea Cantillo is a kind-hearted single mother and recovering addict who becomes Jesse Pinkman’s love interest in the television series "Breaking Bad."
-
D.
Sofia Arreguin
Sofia Arreguin is a member of the creative collective or group known as Wand.
-
E.
Lauren Vélez
Lauren Vélez is an American actress best known for her role as Lieutenant Maria LaGuerta on the television series "Dexter."
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9043f82248190b05692aa0dc178a8 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6684b79c48190a663e9f5504ba20c |
completed | May 2, 2026, 9:10 p.m. |
Created at: April 8, 2026, 9:48 p.m.