Triple

T10077745
Position Surface form Disambiguated ID Type / Status
Subject Fara Williams E213813 entity
Predicate givenName P17 FINISHED
Object Fara E737220 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: Fara | Statement: [Fara Williams, givenName, Fara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fara
Context triple: [Fara Williams, givenName, Fara]
  • A. Fara chosen
    Fara is a character from A. E. van Vogt’s science fiction novel "The Weapon Shops of Isher," set in a far-future empire dominated by the powerful Isher dynasty and its enigmatic weapon dealers.
  • B. Shara
    Shara is an ancient Mesopotamian deity, primarily known as the warrior god and tutelary divine figure associated with the city-state of Umma in Sumer.
  • C. Flisa
    Flisa is a small town in Innlandet county, Norway, known as a local commercial and administrative center in the Glåmdalen region.
  • D. Faiha
    Faiha is a residential district in Kuwait City known for its planned layout, community facilities, and central location within the capital.
  • E. Fata
    Fata are the Roman personifications of fate, equivalent to the Parcae, who determine the destinies and lifespans of humans and gods.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd02f47e08190bfeb641b202beecc completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29ad05bbc8190b103d66c9e786c86 completed April 5, 2026, 5:24 p.m.
Created at: March 30, 2026, 8:59 p.m.