Triple
T2728173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane Darwell |
E60245
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Patti |
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: Patti | Statement: [Jane Darwell, givenName, Patti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Patti Context triple: [Jane Darwell, givenName, Patti]
-
A.
Patty Baker
Patty Baker is a notable individual who shares the surname Baker and has achieved sufficient recognition to be specifically identified among its bearers.
-
B.
Peggy
Peggy is a common diminutive or nickname for the given name Margaret.
-
C.
Patricia
chosen
Patricia is a feminine given name of Latin origin, commonly used in English-speaking countries.
-
D.
Judy
"Judy" is a 2019 biographical drama film in which Renée Zellweger portrays legendary entertainer Judy Garland during her final years, a role that earned her widespread acclaim and major acting awards.
-
E.
Patsy Kelly
Patsy Kelly was an American actress and comedian known for her wisecracking roles in 1930s comedies and later character parts in film, television, and stage.
- 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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdacffa6481909df37335e8fdd595 |
completed | March 7, 2026, 7:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afbbc227c48190b7ab34c6760d3331 |
completed | March 10, 2026, 6:35 a.m. |
Created at: March 6, 2026, 9:56 p.m.