Triple
T22750829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tricia Davis |
E562689
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tricia |
—
|
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: Tricia | Statement: [Tricia Davis, givenName, Tricia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tricia Context triple: [Tricia Davis, givenName, Tricia]
-
A.
Tricia
chosen
Tricia is a feminine given name commonly used as a shortened or informal form of Patricia.
-
B.
Trisha
Trisha is a prominent Indian actress best known for her leading roles in Tamil films and her significant impact on South Indian cinema.
-
C.
Tracy Yvonne
Tracy Yvonne is a film producer best known for her work on the horror-comedy movie "The Blackening."
-
D.
Tracye
Tracye is a person known for being a friend of Shanté Smith.
-
E.
Tracy
Tracy is a city in California’s Central Valley known as a growing suburban community within the San Francisco Bay Area’s commuter belt.
- 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b8e9408190b251700d3386a1b9 |
completed | April 29, 2026, 3:23 a.m. |
Created at: April 17, 2026, 3:24 p.m.