Triple

T32189618
Position Surface form Disambiguated ID Type / Status
Subject Nancy Drew (2019 TV series) E822200 entity
Predicate setting P1957 FINISHED
Object Horseshoe Bay, Maine
Horseshoe Bay, Maine is a fictional small coastal town known as the eerie, mystery-filled backdrop of the 2019 "Nancy Drew" television series.
E1994828 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: Horseshoe Bay, Maine | Statement: [Nancy Drew (2019 TV series), setting, Horseshoe Bay, Maine]
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: Horseshoe Bay, Maine
Triple: [Nancy Drew (2019 TV series), setting, Horseshoe Bay, Maine]
Generated description
Horseshoe Bay, Maine is a fictional small coastal town known as the eerie, mystery-filled backdrop of the 2019 "Nancy Drew" television series.

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_69f3490819cc81909bae1f8ce99423c5 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bacbaa208190b1edec2032701044 completed May 3, 2026, 3:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0be8f28081908226661f2085b22a completed June 14, 2026, 8:15 p.m.
NEDg Description generation batch_6a2f0d243400819094bb3a137a28d65b completed June 14, 2026, 8:20 p.m.
NED2 Entity disambiguation (via description) batch_6a2f0db3ab5c81909697d58fc3becd96 completed June 14, 2026, 8:23 p.m.
Created at: May 1, 2026, 12:35 a.m.