Triple

T94563
Position Surface form Disambiguated ID Type / Status
Subject Håkon Wium Lie E1900 entity
Predicate familyName P18 FINISHED
Object Lie E3160 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: Lie | Statement: [Håkon Wium Lie, familyName, Lie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lie
Context triple: [Håkon Wium Lie, familyName, Lie]
  • A. Lie chosen
    Lie is a Norwegian surname most notably borne by Trygve Lie, the first Secretary-General of the United Nations.
  • B. Statue of Three Lies
    The Statue of Three Lies is the famous bronze monument in Harvard Yard whose inscription contains three historical inaccuracies, making it a well-known campus curiosity and tourist attraction.
  • C. Lee
    Lee is a given name shared by numerous individuals across different cultures and professions.
  • D. The Tender Trap
    The Tender Trap is a 1955 romantic comedy film starring Frank Sinatra and Debbie Reynolds, adapted from the Broadway play of the same name.
  • E. Laz people
    Laz people are an indigenous ethnic group of the South Caucasus and Black Sea coastal region, closely related to Georgians and known for their distinct Laz language and maritime culture.
  • 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_69a24d4862f881908cc8b89d3a78031d completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24fd4777c81909ea9b9a6bd4f7ad5 completed Feb. 28, 2026, 2:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a266ebb994819085fb84dd1d2d25ad completed Feb. 28, 2026, 3:54 a.m.
Created at: Feb. 28, 2026, 2:09 a.m.