Triple

T24521691
Position Surface form Disambiguated ID Type / Status
Subject Clara Mamet E606546 entity
Predicate notableWork P4 FINISHED
Object The Sky Is Everywhere
The Sky Is Everywhere is a coming-of-age drama film written and directed by Clara Mamet, adapted from Jandy Nelson’s novel about a teenage girl coping with grief, love, and self-discovery.
 E1639743 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: The Sky Is Everywhere | Statement: [Clara Mamet, notableWork, The Sky Is Everywhere]
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: The Sky Is Everywhere
Triple: [Clara Mamet, notableWork, The Sky Is Everywhere]
Generated description
The Sky Is Everywhere is a coming-of-age drama film written and directed by Clara Mamet, adapted from Jandy Nelson’s novel about a teenage girl coping with grief, love, and self-discovery.

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_69e2c4c85778819085f5da9af3569ad5 completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a872c120819095c9d50722230d66 completed April 30, 2026, 12:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee96f3bc81909e6ac98964957160 completed May 22, 2026, 5:50 a.m.
NEDg Description generation batch_6a0ff2a66cf08190ad3724f56a0fe84f completed May 22, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff34de0708190ab6f3e978b5feab7 completed May 22, 2026, 6:10 a.m.
Created at: April 18, 2026, 2:24 a.m.