Triple

T26792919
Position Surface form Disambiguated ID Type / Status
Subject Stevie Wayne E670564 entity
Predicate residence P75 FINISHED
Object Antonio Bay
Antonio Bay is the fictional coastal California town haunted by vengeful ghosts in John Carpenter’s 1980 horror film "The Fog."
E1745293 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: Antonio Bay | Statement: [Stevie Wayne, residence, Antonio Bay]
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: Antonio Bay
Triple: [Stevie Wayne, residence, Antonio Bay]
Generated description
Antonio Bay is the fictional coastal California town haunted by vengeful ghosts in John Carpenter’s 1980 horror film "The Fog."

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_69eeb31d45f8819089f52ebdbc556218 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f619bd27908190ac9152693dd37658 completed May 2, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12133015e481908344d2e12aea3406 completed May 23, 2026, 8:50 p.m.
NEDg Description generation batch_6a121588e82881909c65908183417085 completed May 23, 2026, 9 p.m.
NED2 Entity disambiguation (via description) batch_6a121600e8f081909f5deb07266e1a80 completed May 23, 2026, 9:02 p.m.
Created at: April 27, 2026, 4:17 a.m.