Triple

T32140263
Position Surface form Disambiguated ID Type / Status
Subject Managua earthquake of 1972 E820881 entity
Predicate percentageCityDestroyed P176051 FINISHED
Object about 90 percent of city center LITERAL 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: about 90 percent of city center | Statement: [Managua earthquake of 1972, percentageCityDestroyed, about 90 percent of city center]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: percentageCityDestroyed
Context triple: [Managua earthquake of 1972, percentageCityDestroyed, about 90 percent of city center]
  • A. buildingsDamagedOrDestroyedPercentage
    Indicates the proportion of buildings that have been damaged or completely destroyed relative to the total number of buildings in the relevant area or set.
  • B. mainCityDestroyed
    Indicates that the primary or central city associated with an entity has been destroyed.
  • C. destroyedCity
    Indicates that an entity has caused the complete or near-complete destruction of a city.
  • D. numberOfDistrictsDestroyed
    Indicates the quantity of districts that have been destroyed in a given context or event.
  • E. buildingsDestroyed
    Indicates that one or more buildings have been damaged to the point of destruction as a result of some event or action.
  • F. None of above. chosen

Provenance (4 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_69f349039e0c819091c7a7d322e3f46d completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6db6af1d88190989810182354d60f completed May 3, 2026, 5:21 a.m.
PD Predicate disambiguation batch_69f6d82d068c8190940a3200ed760e38 completed May 3, 2026, 5:07 a.m.
PDg Predicate description generation batch_69f6db6a38d881909ecc75cc527910f2 completed May 3, 2026, 5:21 a.m.
Created at: May 1, 2026, 12:30 a.m.