Triple

T30847343
Position Surface form Disambiguated ID Type / Status
Subject 1941 Guerrero earthquake E785674 entity
Predicate relatedTo P37 FINISHED
Object Guerrero seismic gap
The Guerrero seismic gap is a segment of Mexico’s Pacific subduction zone known for its unusually long period without major earthquakes, making it a focus of seismic hazard research.
E1933280 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: Guerrero seismic gap | Statement: [1941 Guerrero earthquake, relatedTo, Guerrero seismic gap]
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: Guerrero seismic gap
Triple: [1941 Guerrero earthquake, relatedTo, Guerrero seismic gap]
Generated description
The Guerrero seismic gap is a segment of Mexico’s Pacific subduction zone known for its unusually long period without major earthquakes, making it a focus of seismic hazard research.

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_69f224b850848190a4af4ccf8ddadcdf completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6917961ec81908dbd73e67c1ff383 completed May 3, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbf8bdac819088923a49b26dbf84 completed June 10, 2026, 1:20 a.m.
NEDg Description generation batch_6a28bc6cb6a881909ed7d6cc6f4d697d completed June 10, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_6a28bd11752881909989925c16498f98 completed June 10, 2026, 1:25 a.m.
Created at: April 29, 2026, 8:46 p.m.