Triple
T15151288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Machete (character) |
E361946
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Carmen Cortez |
E72698
|
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: Carmen Cortez | Statement: [Machete (character), relative, Carmen Cortez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carmen Cortez Context triple: [Machete (character), relative, Carmen Cortez]
-
A.
Carmen Cortez
chosen
Carmen Cortez is a resourceful young spy and one of the two sibling protagonists in the Spy Kids film series.
-
B.
Carmen Vasquez
Carmen Vasquez is a supporting character in the 2000 crime-action film "Shaft," involved in the investigation led by detective John Shaft.
-
C.
Lola Flores
Lola Flores was a celebrated Spanish flamenco singer, dancer, and actress, iconic in 20th-century Spanish popular culture.
-
D.
Juni Cortez
Juni Cortez is a young, tech-savvy secret agent and one of the sibling protagonists in the Spy Kids film series.
-
E.
Delia Ramirez
Delia Ramirez is an American politician and community organizer from Illinois who serves as a Democratic member of the U.S. House of Representatives.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00609040081908c849475a2fa6443 |
completed | April 15, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef64dbfc819098dac50500673ed4 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3:07 a.m.