Triple

T10015473
Position Surface form Disambiguated ID Type / Status
Subject Patricia Russo E199480 entity
Predicate boardMemberOf P10 FINISHED
Object Hewlett-Packard E7429 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: Hewlett-Packard | Statement: [Patricia Russo, boardMemberOf, Hewlett-Packard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hewlett-Packard
Context triple: [Patricia Russo, boardMemberOf, Hewlett-Packard]
  • A. Hewlett-Packard chosen
    Hewlett-Packard is a pioneering American technology company known for its innovations in computing, printers, and enterprise IT solutions.
  • B. Hewlett Packard Enterprise
    Hewlett Packard Enterprise is a major American multinational enterprise IT company that provides servers, storage, networking, and related services to business and government customers worldwide.
  • C. Compaq
    Compaq was a major American computer company best known for its popular line of personal computers and for being one of the largest PC manufacturers before its acquisition by Hewlett-Packard.
  • D. IBM
    IBM is a multinational technology and consulting company known for its pioneering work in computer hardware, software, and enterprise services.
  • E. Dell
    Dell is a major American technology company best known for designing, manufacturing, and selling personal computers, servers, and related IT products and services worldwide.
  • 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_69ca8315a1a08190ab310f25620f362b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd4ad3348190bae03cd37c787674 completed April 2, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69d26a99971081908397f06c0ce913d0 completed April 5, 2026, 1:58 p.m.
Created at: March 30, 2026, 8:52 p.m.