Triple

T37741990
Position Surface form Disambiguated ID Type / Status
Subject Suzie, Do You Copy? E940738 entity
Predicate locationOfAction P20834 FINISHED
Object Hopper’s cabin
Hopper’s cabin is the secluded woodland home of Chief Jim Hopper and Eleven in the TV series "Stranger Things," serving as a central setting for many key events.
E2241059 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: Hopper’s cabin | Statement: [Suzie, Do You Copy?, locationOfAction, Hopper’s cabin]
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: Hopper’s cabin
Triple: [Suzie, Do You Copy?, locationOfAction, Hopper’s cabin]
Generated description
Hopper’s cabin is the secluded woodland home of Chief Jim Hopper and Eleven in the TV series "Stranger Things," serving as a central setting for many key events.

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_69f76ee0e32c8190b40a3b4cf590337c completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbaebf2868819089b2e6ff81c572c9 completed May 6, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40d68b97148190bb8c32ef52c04166 completed June 28, 2026, 8:08 a.m.
NEDg Description generation batch_6a40d91253708190adda9862af4982fc completed June 28, 2026, 8:19 a.m.
NED2 Entity disambiguation (via description) batch_6a40d99432948190b0cae08995c02108 completed June 28, 2026, 8:21 a.m.
Created at: May 3, 2026, 4:18 p.m.