Triple

T1326145
Position Surface form Disambiguated ID Type / Status
Subject Kathleen E28330 entity
Predicate hasShortForm P43 FINISHED
Object Kat E151965 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: Kat | Statement: [Kathleen, hasShortForm, Kat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kat
Context triple: [Kathleen, hasShortForm, Kat]
  • A. Kat chosen
    Kat is a given name, typically used as a shortened or informal form of Kathleen or Katherine.
  • B. Karen
    Karen is a common feminine given name used in many English-speaking and European countries.
  • C. Karen
    The Karen are an indigenous ethnic group of Southeast Asia, primarily living in Myanmar and Thailand, with distinct languages, cultures, and a long history of political struggle and displacement.
  • D. Ka
    Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
  • E. Kip
    Kip is a young Sikh British-Indian army sapper in Michael Ondaatje’s novel "The English Patient," whose expertise in bomb disposal and complex relationship with the other characters explore themes of war, identity, and colonialism.
  • 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_69a498540a2481909e807a762280d3ba completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c19fd2648190932a85eacb3e7ec4 completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc62764d88190b7d1fca10835f560 completed March 8, 2026, 12:43 a.m.
Created at: March 1, 2026, 7:55 p.m.