Triple

T2735606
Position Surface form Disambiguated ID Type / Status
Subject Herzliya E60622 entity
Predicate hasCompanyPresence P17483 FINISHED
Object HP (offices/R&D) 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: HP (offices/R&D) | Statement: [Herzliya, hasCompanyPresence, HP (offices/R&D)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HP (offices/R&D)
Context triple: [Herzliya, hasCompanyPresence, HP (offices/R&D)]
  • A. Hewlett-Packard chosen
    Hewlett-Packard is a pioneering American technology company known for its innovations in computing, printers, and enterprise IT solutions.
  • B. HP
    HP is the vehicle registration code used on motor vehicles registered in the Indian state of Himachal Pradesh.
  • C. IBM
    IBM is a multinational technology and consulting company known for its pioneering work in computer hardware, software, and enterprise services.
  • D. HCL Technologies
    HCL Technologies is a global Indian IT services and consulting company known for providing software development, infrastructure management, and digital transformation solutions to enterprises worldwide.
  • E. Perot Systems
    Perot Systems was an American information technology services and consulting company founded by Ross Perot that provided outsourcing, systems integration, and technology solutions to businesses and governments 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_69ab4b77febc819095603eb012cd141b completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb1022488190af84e536946b2e37 completed March 7, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb6a37fdc8190bcdb33d7352d9e16 completed March 10, 2026, 6:13 a.m.
Created at: March 6, 2026, 9:56 p.m.