Triple

T36437098
Position Surface form Disambiguated ID Type / Status
Subject San Juan E897614 entity
Predicate historicalEvent P259 FINISHED
Object 1944 San Juan earthquake
The 1944 San Juan earthquake was a devastating seismic event in western Argentina that caused widespread destruction in the city of San Juan and led to major changes in the country’s building codes and urban planning.
E2183186 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: 1944 San Juan earthquake | Statement: [San Juan, historicalEvent, 1944 San Juan earthquake]
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: 1944 San Juan earthquake
Triple: [San Juan, historicalEvent, 1944 San Juan earthquake]
Generated description
The 1944 San Juan earthquake was a devastating seismic event in western Argentina that caused widespread destruction in the city of San Juan and led to major changes in the country’s building codes and urban planning.

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_69f76e56636481908eda808ab0273401 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd6acacc8190a78ddc317d85db35 completed May 3, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39c418376481909c4dd8d68b1f44ee completed June 22, 2026, 11:24 p.m.
NEDg Description generation batch_6a39c48912548190bd632d5e355f3cb2 completed June 22, 2026, 11:26 p.m.
NED2 Entity disambiguation (via description) batch_6a39c55c9d188190b9a5dab4ca8036e8 completed June 22, 2026, 11:29 p.m.
Created at: May 3, 2026, 4:10 p.m.