Triple
T20840192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wallace Beery |
E513074
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Rita Gilman |
E513074
|
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: Rita Gilman | Statement: [Wallace Beery, spouse, Rita Gilman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rita Gilman Context triple: [Wallace Beery, spouse, Rita Gilman]
-
A.
Rita Gilman
chosen
Rita Gilman was the wife of American film actor Wallace Beery, known primarily for her marriage to the prominent Hollywood star.
-
B.
Rita DeMara
Rita DeMara is a Marvel Comics character who becomes the supervillain-turned-hero Yellowjacket, known for her size-changing abilities and complex moral journey.
-
C.
Rita Weiman
Rita Weiman was an American writer and playwright known for her short stories and screenwriting work in early 20th-century film and theater.
-
D.
Rita Ryack
Rita Ryack is an American costume designer known for her elaborate, character-driven work on films such as "How the Grinch Stole Christmas" (2000).
-
E.
Lisa Banes
Lisa Banes was an American stage, film, and television actress known for her versatile character roles in productions such as "Gone Girl," "Cocktail," and numerous Broadway and TV appearances.
- 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_69e0b4cf62a88190bbf92351e9e57259 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c34a60848190b33078172675f8d7 |
completed | April 21, 2026, 12:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a2eb705288190a77bdd249e57f869 |
completed | May 17, 2026, 9:10 p.m. |
Created at: April 16, 2026, 12:43 p.m.