Triple
T18810049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solares Hill |
E459985
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Victorio Solares |
—
|
NE NERFINISHED |
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: Victorio Solares | Statement: [Solares Hill, namedAfter, Victorio Solares]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Victorio Solares Context triple: [Solares Hill, namedAfter, Victorio Solares]
-
A.
Victorio Solares
chosen
Victorio Solares was a notable local figure after whom Solares Hill in Key West, Florida, was named, reflecting his significance in the area’s history or development.
-
B.
Victor Salazar
Victor Salazar is the teenage protagonist of the TV series "Love, Victor," which follows his journey of self-discovery, relationships, and coming to terms with his sexual identity.
-
C.
Enrique Arce
Enrique Arce is a Spanish actor best known internationally for his role as the unscrupulous Arturo Román in the hit series "Money Heist."
-
D.
Victor Rojas
Victor Rojas is an actor known for appearing in the romantic comedy-drama film "It Could Happen to You."
-
E.
Pablo Galindo
Pablo Galindo is a Python core developer and software engineer known for his work on the language’s internals, including co-authoring structural pattern matching (PEP 634) and contributing extensively to CPython.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3db38ec8190ab5bef15bc6789be |
completed | April 20, 2026, 3:56 a.m. |
Created at: April 10, 2026, 11:53 a.m.