Triple

T26701730
Position Surface form Disambiguated ID Type / Status
Subject Xander Berkeley E673173 entity
Predicate notableWork P4 FINISHED
Object Salem
"Salem" is a supernatural horror television series that reimagines the infamous Salem witch trials with a dark, fictionalized narrative.
E444348 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: Salem | Statement: [Xander Berkeley, notableWork, Salem]
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: Salem
Triple: [Xander Berkeley, notableWork, Salem]
Generated description
"Salem" is a supernatural horror television series that reimagines the infamous Salem witch trials with a dark, fictionalized narrative.

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_69eecda2b49c8190a6c481cfc4c07954 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f61780706c8190bb9eb3d467d9f852 completed May 2, 2026, 3:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11fe84649481909fb7c264323dfb9a completed May 23, 2026, 7:22 p.m.
NEDg Description generation batch_6a11ff162d588190a1f98429d7fe5154 completed May 23, 2026, 7:25 p.m.
NED2 Entity disambiguation (via description) batch_6a11ff99fdbc81909fd5646fb32987a2 completed May 23, 2026, 7:27 p.m.
Created at: April 27, 2026, 3:32 a.m.