Triple

T1481965
Position Surface form Disambiguated ID Type / Status
Subject Travis Kalanick E30977 entity
Predicate name P16 FINISHED
Object Travis Kalanick E30977 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: Travis Kalanick | Statement: [Travis Kalanick, name, Travis Kalanick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Travis Kalanick
Context triple: [Travis Kalanick, name, Travis Kalanick]
  • A. Travis Kalanick chosen
    Travis Kalanick is an American entrepreneur best known as the co-founder and former CEO of the ride-hailing company Uber.
  • B. Brian Chesky
    Brian Chesky is an American entrepreneur and co-founder/CEO of Airbnb, a leading global home-sharing and travel marketplace.
  • C. Tony Hsieh
    Tony Hsieh was an American entrepreneur and venture capitalist best known for transforming Zappos into a pioneering online retailer celebrated for its customer service–driven culture.
  • D. Martin Eberhard
    Martin Eberhard is an American engineer and entrepreneur best known as a co-founder and early leader of the electric vehicle company Tesla.
  • E. JB Straubel
    JB Straubel is an American engineer and entrepreneur best known as a co-founder and longtime chief technology officer of Tesla, where he played a key role in advancing electric vehicle and battery technologies.
  • 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_69a498fe55a88190ab7f9e40ace88e49 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c6782f088190930d25a56161e2b3 completed March 1, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad15b1bea08190a1e21ddc15148d3a completed March 8, 2026, 6:22 a.m.
Created at: March 1, 2026, 8:11 p.m.