Triple

T2385959
Position Surface form Disambiguated ID Type / Status
Subject Kip E48823 entity
Predicate nickname P55 FINISHED
Object Kip E248929 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: Kip | Statement: [Kip, nickname, Kip]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kip
Context triple: [Kip, nickname, Kip]
  • A. Kip chosen
    Kip is the given name of Kip Thorne, the Nobel Prize–winning American theoretical physicist known for his work on gravitational physics and astrophysics.
  • B. 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.
  • C. Kai
    Kai is the eldest granddaughter of former U.S. President Donald Trump and the daughter of Donald Trump Jr.
  • D. Kiko
    Kiko is the young, albino giant ape who serves as the gentle offspring and companion of King Kong in the 1933 film "Son of Kong."
  • E. Kenneth
    Kenneth is the formal given name of American country music singer, songwriter, and actor Kenny Rogers.
  • 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_69a88aa5f63081908d07fd302029fcbd completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc7d9d8148190bb8aa16fd4364aba completed March 7, 2026, 6:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea8bcb8c88190b57fd4d0a76209a5 completed March 9, 2026, 11:02 a.m.
Created at: March 4, 2026, 7:57 p.m.