Triple

T6987783
Position Surface form Disambiguated ID Type / Status
Subject Guy de Montfort, Count of Nola E162006 entity
Predicate associatedWithPlace P2830 FINISHED
Object Nola E39229 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: Nola | Statement: [Guy de Montfort, Count of Nola, associatedWithPlace, Nola]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nola
Context triple: [Guy de Montfort, Count of Nola, associatedWithPlace, Nola]
  • A. Nola chosen
    Nola is an ancient town in southern Italy, historically significant in Roman times and known as the place where Emperor Augustus died.
  • B. New Orleans
    New Orleans is a historic port city in southeastern Louisiana known for its vibrant jazz music, Creole cuisine, and distinctive French and Spanish-influenced architecture.
  • C. Shreveport
    Shreveport is a major city in northwestern Louisiana known for its role as a regional commercial, cultural, and transportation hub.
  • D. Biloxi
    Biloxi is a coastal Mississippi city known for its beaches, casinos, and seafood industry along the Gulf of Mexico.
  • E. New Iberia
    New Iberia is a small city in southern Louisiana, United States, known for its Cajun and Creole culture, historic architecture, and proximity to the Bayou Teche.
  • 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_69c68856d7808190ab33ee914640281b completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db95c6148190bdb5f355ac04db3f completed March 27, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a110ca08190be2aa78948379495 completed March 28, 2026, 5:41 a.m.
Created at: March 27, 2026, 2:32 p.m.