Triple
T15814682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luna Lauren Vélez |
E383444
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Luna Lauren Vélez |
E383444
|
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: Luna Lauren Vélez | Statement: [Luna Lauren Vélez, name, Luna Lauren Vélez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luna Lauren Vélez Context triple: [Luna Lauren Vélez, name, Luna Lauren Vélez]
-
A.
Luna Lauren Vélez
chosen
Luna Lauren Vélez is an American actress known for her roles in television series like "Dexter" and "New York Undercover" and for voicing Rio Morales in "Spider-Man: Into the Spider-Verse."
-
B.
Rosa Vasquez
Rosa Vasquez is a foster mother in DC Comics’ Shazam! stories who, along with her husband Victor, cares for Billy Batson and the rest of the Shazam family.
-
C.
Lela Cortines
Lela Cortines is an actress known for playing the character Ellie Winston.
-
D.
Marisa Ventura
Marisa Ventura is the hardworking hotel maid and single mother who becomes the romantic lead in the film "Maid in Manhattan."
-
E.
Melina Gallo
Melina Gallo is the wife of Goo Goo Dolls frontman John Rzeznik.
- 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0c4a1571881909488728f123865ad |
completed | April 16, 2026, 11:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb7f3c9481908bdde67998263c5e |
completed | May 10, 2026, 2:20 a.m. |
Created at: April 10, 2026, 4:49 a.m.