Triple
T8428283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | She Wolf |
E199055
|
entity |
| Predicate | musicVideoDirector |
P4911
|
FINISHED |
| Object | Jake Nava |
E69967
|
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: Jake Nava | Statement: [She Wolf, musicVideoDirector, Jake Nava]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jake Nava Context triple: [She Wolf, musicVideoDirector, Jake Nava]
-
A.
Jake Nava
chosen
Jake Nava is a British music video director known for his visually striking work with major artists across pop and R&B.
-
B.
Mike Navarro
Mike Navarro is a relative of American guitarist Dave Navarro, known for his work with Jane's Addiction and the Red Hot Chili Peppers.
-
C.
Chris Núñez
Chris Núñez is a renowned American tattoo artist and television personality best known for co-hosting the reality competition series "Miami Ink" and serving as a judge on "Ink Master."
-
D.
Mark Dacascos
Mark Dacascos is an American actor and martial artist known for his roles in action films and television, as well as for serving as the Chairman on the TV show "Iron Chef America."
-
E.
Javier Navarro
Javier Navarro is a personal name shared by multiple individuals, including professionals and public figures in various fields.
- 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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbd124378c819086ea2fa6ecbfffe1 |
completed | March 31, 2026, 1:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce0376b4708190b2d118bcdf1a00fc |
completed | April 2, 2026, 5:49 a.m. |
Created at: March 30, 2026, 6:07 p.m.