Triple
T13257762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patricia Velásquez |
E315706
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Patricia |
E58034
|
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: Patricia | Statement: [Patricia Velásquez, givenName, Patricia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Patricia Context triple: [Patricia Velásquez, givenName, Patricia]
-
A.
Patricia
chosen
Patricia is a feminine given name of Latin origin, commonly used in English-speaking countries.
-
B.
Patricia Grace
Patricia Grace is a pioneering New Zealand Māori writer renowned for her short stories and novels that foreground Māori perspectives and culture.
-
C.
Jacqueline
Jacqueline is a feminine given name most famously borne by former U.S. First Lady Jacqueline Kennedy Onassis.
-
D.
Patricia Rae
Patricia Rae is an American actress best known for her role in the ensemble romantic comedy film "The Big Wedding."
-
E.
Patricia Avery
Patricia Avery was the wife of influential American animator and director Tex Avery, known for her connection to his life and career in classic Hollywood animation.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98f7614fc8190a1cac076d706e9aa |
completed | April 11, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7546e0b148190a78e6da408347690 |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:25 p.m.