Triple

T13319983
Position Surface form Disambiguated ID Type / Status
Subject Lisa Su E317289 entity
Predicate name P16 FINISHED
Object Lisa Su E317289 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: Lisa Su | Statement: [Lisa Su, name, Lisa Su]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lisa Su
Context triple: [Lisa Su, name, Lisa Su]
  • A. Lisa Su chosen
    Lisa Su is a Taiwanese-American electrical engineer and business executive best known for leading AMD’s turnaround and growth as its chief executive.
  • B. Greg Zeschuk
    Greg Zeschuk is a Canadian video game developer and physician best known as a co-founder of the acclaimed role-playing game studio BioWare.
  • C. Linda Gelsinger
    Linda Gelsinger is the wife of Intel CEO Pat Gelsinger and is known for her involvement in Christian ministry and family-focused activities alongside her husband.
  • D. Diane Greene
    Diane Greene is a prominent American technology executive and entrepreneur best known as a co-founder and former CEO of VMware and a former CEO of Google Cloud.
  • E. Angela Ahrendts
    Angela Ahrendts is an American business executive best known for leading Burberry as CEO and later serving as Apple’s Senior Vice President of Retail.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990faa95481908a7fd297959c062e completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716ee695c81909ffeeb0901ee66c1 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:29 p.m.