Triple

T5035351
Position Surface form Disambiguated ID Type / Status
Subject Laura Archera Huxley E113406 entity
Predicate placeOfBirth P1 FINISHED
Object Turin, Italy E15144 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: Turin, Italy | Statement: [Laura Archera Huxley, placeOfBirth, Turin, Italy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turin, Italy
Context triple: [Laura Archera Huxley, placeOfBirth, Turin, Italy]
  • A. Turin chosen
    Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and economic hub.
  • B. Turin
    Turin is a small town located in Coweta County in the U.S. state of Georgia.
  • C. Metropolitan City of Turin
    The Metropolitan City of Turin is an Italian administrative region in Piedmont that encompasses the city of Turin and its surrounding municipalities, coordinating local governance, infrastructure, and regional development.
  • D. Tivoli, Italy
    Tivoli, Italy is a historic town near Rome renowned for its ancient villas, spectacular gardens, and scenic waterfalls.
  • E. Milan
    Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73b9ad488190a2a8c4da8858eb91 completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba5b5f84819086b7af26923f0987 completed March 21, 2026, 3:33 p.m.
Created at: March 20, 2026, 1:36 p.m.