Triple

T37107463
Position Surface form Disambiguated ID Type / Status
Subject Academy Award for Best Supporting Actress for Olympia Dukakis E918884 entity
Predicate forRole P133192 FINISHED
Object Rose Castorini
Rose Castorini is the sharp-tongued, no-nonsense Brooklyn matriarch portrayed by Olympia Dukakis in the romantic comedy film "Moonstruck."
E2241298 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: Rose Castorini | Statement: [Academy Award for Best Supporting Actress for Olympia Dukakis, forRole, Rose Castorini]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rose Castorini
Triple: [Academy Award for Best Supporting Actress for Olympia Dukakis, forRole, Rose Castorini]
Generated description
Rose Castorini is the sharp-tongued, no-nonsense Brooklyn matriarch portrayed by Olympia Dukakis in the romantic comedy film "Moonstruck."

Provenance (5 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_69f76e9b99c8819096164b21ff5bd996 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb2ff33cac819080169be5adb7451d completed May 6, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40d65d5c908190baa115e2d6ea97f9 completed June 28, 2026, 8:07 a.m.
NEDg Description generation batch_6a40da02ae60819085c5d8e91f32a767 completed June 28, 2026, 8:23 a.m.
NED2 Entity disambiguation (via description) batch_6a40db6c36a081909d09f57e06f37993 completed June 28, 2026, 8:29 a.m.
Created at: May 3, 2026, 4:14 p.m.