Triple

T4875166
Position Surface form Disambiguated ID Type / Status
Subject Juan Luis Cipriani Thorne E109183 entity
Predicate familyName P18 FINISHED
Object Thorne E244848 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: Thorne | Statement: [Juan Luis Cipriani Thorne, familyName, Thorne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thorne
Context triple: [Juan Luis Cipriani Thorne, familyName, Thorne]
  • A. Thorne chosen
    Thorne is a surname most prominently associated with Kip Thorne, the Nobel Prize–winning theoretical physicist known for his work on gravitation and black holes.
  • B. Thorney
    Thorney is a village in Cambridgeshire, England, historically centered around its important medieval Benedictine abbey.
  • C. Taffs Well
    Taffs Well is a village in South Wales known for its historic thermal spring and proximity to Cardiff at the southern end of the Taff Valley.
  • D. Thornbury
    Thornbury is a historic market town in South Gloucestershire, England, known for its medieval castle and traditional high street.
  • E. Bramber
    Bramber is a historic village in West Sussex, England, known for the ruins of Bramber Castle and its picturesque rural setting.
  • 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_69bd440e9d64819083e82cf33b4d9570 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6da1b45881909d45cb1214f5bdde completed March 20, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67f90e848190a36eee1e670657e4 completed March 21, 2026, 9:42 a.m.
Created at: March 20, 2026, 1:27 p.m.