Triple

T30401731
Position Surface form Disambiguated ID Type / Status
Subject Rebecca Henderson E773366 entity
Predicate notableWork P4 FINISHED
Object They Remain
They Remain is a 2018 psychological horror film, adapted from Laird Barron’s short story “-30-,” about two scientists investigating mysterious phenomena at a remote former cult compound.
E1913894 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: They Remain | Statement: [Rebecca Henderson, notableWork, They Remain]
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: They Remain
Triple: [Rebecca Henderson, notableWork, They Remain]
Generated description
They Remain is a 2018 psychological horror film, adapted from Laird Barron’s short story “-30-,” about two scientists investigating mysterious phenomena at a remote former cult compound.

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_69f2248facd48190b183c3f3ca6daef7 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68619900c8190b8fcaaeb0c936da9 completed May 2, 2026, 11:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2789589f7c8190833bb3c638433f77 completed June 9, 2026, 3:32 a.m.
NEDg Description generation batch_6a278a5d184081908fbaf650cb44e2b7 completed June 9, 2026, 3:37 a.m.
NED2 Entity disambiguation (via description) batch_6a278cda6ab8819097cd6e2f0b1124c1 completed June 9, 2026, 3:47 a.m.
Created at: April 29, 2026, 8:03 p.m.