Triple
T10537217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chavez Ravine |
E248599
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Julian Chavez |
E248599
|
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: Julian Chavez | Statement: [Chavez Ravine, namedAfter, Julian Chavez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julian Chavez Context triple: [Chavez Ravine, namedAfter, Julian Chavez]
-
A.
Julian Chavez
chosen
Julian Chavez was a 19th-century Los Angeles city councilman and landowner whose name was given to the area later known as Chavez Ravine.
-
B.
Ricardo Chávez
Ricardo Chávez is a Mexican actor known for his work in telenovelas and film.
-
C.
Juan Chávez
Juan Chávez is a personal name shared by multiple individuals, most commonly associated with Latin American figures in politics, sports, and public life.
-
D.
Sergio Chávez
Sergio Chávez is a personal name that may refer to multiple individuals, including professionals and public figures in Spanish-speaking countries.
-
E.
Carlos Ochoa
Carlos Ochoa 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a554fb4819081e9618bab051dc6 |
completed | April 7, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e8a6567f14819086134cdf3a13aa9b |
completed | April 22, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:31 p.m.