Triple

T5222869
Position Surface form Disambiguated ID Type / Status
Subject fall of Mantua E117912 entity
Predicate hasLocation P40 FINISHED
Object Mantua E68502 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: Mantua | Statement: [fall of Mantua, hasLocation, Mantua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mantua
Context triple: [fall of Mantua, hasLocation, Mantua]
  • A. Mantua
    Mantua is a residential neighborhood in West Philadelphia known for its historic rowhouses and proximity to major universities and cultural institutions.
  • B. Mantua
    Mantua is a small Cuban town and municipality located in the western part of Pinar del Río Province.
  • C. Mantua chosen
    Mantua is a historic city in northern Italy’s Lombardy region, renowned for its Renaissance architecture, artistic heritage, and former status as the seat of the Gonzaga dynasty.
  • D. Verona
    Verona is a historic city in northern Italy renowned for its well-preserved Roman architecture and its association with Shakespeare’s "Romeo and Juliet."
  • E. Cremona
    Cremona is a historic city in northern Italy renowned for its tradition of violin making and its well-preserved medieval architecture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69bd4465e03081909bfcfd7113062590 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7abba82881908c030ba55146b8ea completed March 20, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf486fb3f48190a07829bcb9d0f521 completed March 22, 2026, 1:39 a.m.
Created at: March 20, 2026, 1:48 p.m.