Triple

T32954285
Position Surface form Disambiguated ID Type / Status
Subject Elsinore Fault Zone E843052 entity
Predicate segment P889 FINISHED
Object Temecula segment
The Temecula segment is a section of Southern California’s Elsinore Fault Zone, a major right-lateral strike-slip fault system capable of generating significant earthquakes.
E2031132 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: Temecula segment | Statement: [Elsinore Fault Zone, segment, Temecula segment]
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: Temecula segment
Triple: [Elsinore Fault Zone, segment, Temecula segment]
Generated description
The Temecula segment is a section of Southern California’s Elsinore Fault Zone, a major right-lateral strike-slip fault system capable of generating significant earthquakes.

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_69f3494a31f481909057136e49b4fe60 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d17171388190b37fb7268a80b569 completed May 3, 2026, 4:39 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34d2763e848190b212c5116e1ba74a completed June 19, 2026, 5:24 a.m.
NEDg Description generation batch_6a34d41717c0819092c139f8f9f91b90 completed June 19, 2026, 5:31 a.m.
NED2 Entity disambiguation (via description) batch_6a34d47fb1e481908499ef7f96592128 completed June 19, 2026, 5:32 a.m.
Created at: May 1, 2026, 1:21 a.m.