Triple

T33458626
Position Surface form Disambiguated ID Type / Status
Subject Mass Appeal E856846 entity
Predicate mainCharacter P1183 FINISHED
Object Father Tim Farley
Father Tim Farley is the witty, world-weary Catholic priest at the center of the stage play and film "Mass Appeal," whose relationship with a zealous young seminarian drives the story’s exploration of faith, doubt, and church politics.
E2052217 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: Father Tim Farley | Statement: [Mass Appeal, mainCharacter, Father Tim Farley]
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: Father Tim Farley
Triple: [Mass Appeal, mainCharacter, Father Tim Farley]
Generated description
Father Tim Farley is the witty, world-weary Catholic priest at the center of the stage play and film "Mass Appeal," whose relationship with a zealous young seminarian drives the story’s exploration of faith, doubt, and church politics.

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_69f3497281a08190b4705de0b5f26ba7 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e4d0a7a8819090026ef0c5265f9e completed May 3, 2026, 6:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a358169c4fc819097296992126a6319 completed June 19, 2026, 5:50 p.m.
NEDg Description generation batch_6a35857c0008819092ad90f2d9aa4bba completed June 19, 2026, 6:07 p.m.
NED2 Entity disambiguation (via description) batch_6a358a6e3500819082641146aec17075 completed June 19, 2026, 6:29 p.m.
Created at: May 1, 2026, 1:37 a.m.