Triple
T12905518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scenes from an Italian Restaurant |
E308719
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Brenda |
E452857
|
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: Brenda | Statement: [Scenes from an Italian Restaurant, featuresCharacter, Brenda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brenda Context triple: [Scenes from an Italian Restaurant, featuresCharacter, Brenda]
-
A.
Brenda
chosen
Brenda is a feminine given name commonly used in English-speaking countries.
-
B.
Bridgette
Bridgette is a feminine given name commonly used in English-speaking countries, often considered a variant of "Bridget."
-
C.
Bobbie
Bobbie is a character in the 1971 drama film "Carnal Knowledge," which explores the evolving sexual and emotional relationships of two college friends over several decades.
-
D.
Bobbie
Bobbie is the nickname of Bobbie Rosenfeld, a celebrated Canadian track and field athlete and Olympic gold medalist.
-
E.
Sandra
Sandra is the given name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971831bd48190b0ecd13e7181bbc6 |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a565ce508190a73f33708e61dc7d |
completed | May 3, 2026, 1:31 a.m. |
Created at: April 9, 2026, 5:41 p.m.