Triple

T21407150
Position Surface form Disambiguated ID Type / Status
Subject Avetrana E528066 entity
Predicate locatedNear P294 FINISHED
Object Manduria NE NERFINISHED

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: Manduria | Statement: [Avetrana, locatedNear, Manduria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manduria
Context triple: [Avetrana, locatedNear, Manduria]
  • A. Manduria chosen
    Manduria is a historic town in Italy’s Apulia region, renowned for its ancient Messapian archaeological sites and production of Primitivo di Manduria wine.
  • B. Mandurama
    Mandurama is a small rural village in the Central West region of New South Wales, Australia, known for its agricultural surroundings and historic buildings.
  • C. Martos
    Martos is a historic town in southern Spain’s Andalusia region, known for its olive oil production and hilltop setting dominated by a medieval castle.
  • D. M’Sila
    M’Sila is a city in north-central Algeria that serves as the capital of M’Sila Province and a regional hub for agriculture and trade.
  • E. Mazzanta
    Mazzanta is a coastal locality and seaside resort area within the municipality of Rosignano Marittimo in Tuscany, Italy.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b520ee3c8190abddbee7e37e834c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b1b1acd881908556981ed788340c completed April 22, 2026, 11:32 a.m.
Created at: April 16, 2026, 5:32 p.m.