Triple

T9414805
Position Surface form Disambiguated ID Type / Status
Subject Tinsukia E226989 entity
Predicate hasNearbyTown P3883 FINISHED
Object Margherita E686754 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: Margherita | Statement: [Tinsukia, hasNearbyTown, Margherita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margherita
Context triple: [Tinsukia, hasNearbyTown, Margherita]
  • A. Margherita
    Margherita is the Italian form of the female given name Margaret, commonly used in Italy and other Italian-speaking communities.
  • B. Margherita chosen
    Margherita is a coal-mining town in Assam, India, known for its tea gardens and proximity to the Patkai hills near the India–Myanmar border.
  • C. pizza Margherita
    Pizza Margherita is a classic Italian pizza topped with tomatoes, mozzarella, fresh basil, and olive oil, symbolizing the colors of the Italian flag.
  • D. Caprese
    Caprese is a small Tuscan village in Italy best known as the birthplace of the Renaissance artist Michelangelo.
  • E. Neapolitan
    Neapolitan is a Romance language spoken in and around Naples and much of southern Italy, known for its distinct phonology, vocabulary, and rich literary and musical traditions.
  • 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_69ca84359e7c819091148ba4b670e436 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd68c7bd648190b17f082883c98239 completed April 1, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69d107b63cf48190a072e3434a7b85a8 completed April 4, 2026, 12:44 p.m.
Created at: March 30, 2026, 7:47 p.m.