Triple

T23744652
Position Surface form Disambiguated ID Type / Status
Subject Take Shelter E586779 entity
Predicate mainCharacter P1183 FINISHED
Object Curtis LaForche
Curtis LaForche is the troubled Ohio family man in the psychological drama "Take Shelter," whose apocalyptic visions drive him to obsessively build a storm shelter as he questions his own sanity.
E1612563 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: Curtis LaForche | Statement: [Take Shelter, mainCharacter, Curtis LaForche]
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: Curtis LaForche
Triple: [Take Shelter, mainCharacter, Curtis LaForche]
Generated description
Curtis LaForche is the troubled Ohio family man in the psychological drama "Take Shelter," whose apocalyptic visions drive him to obsessively build a storm shelter as he questions his own sanity.

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_69e24908efb08190bf755c3a9b91f222 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bcbcc4f88190a00fceeafbfb5cfd completed April 29, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7e50b0b08190a330944b0f5ee279 completed May 21, 2026, 9:51 p.m.
NEDg Description generation batch_6a0f7f21e3608190b646947083391923 completed May 21, 2026, 9:54 p.m.
NED2 Entity disambiguation (via description) batch_6a0f7fc9437c8190999551269a49fb65 completed May 21, 2026, 9:57 p.m.
Created at: April 17, 2026, 7:12 p.m.