Triple

T19143509
Position Surface form Disambiguated ID Type / Status
Subject Beg Khan E468616 entity
Predicate relatedToTitle P5175 FINISHED
Object Bek 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: Bek | Statement: [Beg Khan, relatedToTitle, Bek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bek
Context triple: [Beg Khan, relatedToTitle, Bek]
  • A. Bek chosen
    Bek is a short or informal given name, typically used as a diminutive of Rebekah.
  • B. Bem
    Bem is a character from the "What Where" segment of Samuel Beckett’s television play, representing one of the indistinct figures involved in its cryptic, minimalist drama.
  • C. Bey
    A Bey was a provincial governor or chieftain in the Ottoman Empire, often wielding significant military and administrative authority.
  • D. BEK
    BEK is the IATA airport code for Bareilly Airport, a domestic airport serving the city of Bareilly in Uttar Pradesh, India.
  • E. Beketaten
    Beketaten was an ancient Egyptian princess of the 18th Dynasty, likely a daughter of Pharaoh Amenhotep III and Queen Tiye, who lived during the Amarna period.
  • 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_69d8dd0796a48190b34ce4cd9d3f3be5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e977fa208190aa8cafd0966599c6 completed April 20, 2026, 8:53 a.m.
Created at: April 10, 2026, 12:05 p.m.