Triple
T10007297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shameika |
E198284
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | David Garza |
E840057
|
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: David Garza | Statement: [Shameika, producer, David Garza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Garza Context triple: [Shameika, producer, David Garza]
-
A.
David Garza
chosen
David Garza is an American musician, songwriter, and record producer known for his eclectic solo work and collaborations with artists such as Fiona Apple.
-
B.
Jaime Garza
Jaime Garza is a Mexican actor best known for his work in telenovelas and films during the late 20th century.
-
C.
Joe Garza
Joe Garza is a relatively obscure individual whose name is shared with several people, including professionals in fields such as law, politics, and the arts.
-
D.
Tony Garza
Tony Garza is an American attorney and former U.S. Ambassador to Mexico known for his work in diplomacy and U.S.–Mexico relations.
-
E.
Xavier Garza
Xavier Garza is a Mexican American author and illustrator known for his bilingual children’s books and stories that draw on Chicano culture, folklore, and everyday life in South Texas.
- 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_69ca830fcca48190bbbd9b20c233835f |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd187fe481908556ea896c528ea4 |
completed | April 2, 2026, 1:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d30020305c81909c4fb01291c70cb6 |
completed | April 6, 2026, 12:36 a.m. |
Created at: March 30, 2026, 8:52 p.m.