Triple

T20405111
Position Surface form Disambiguated ID Type / Status
Subject Kista E500446 entity
Predicate hasMajorCompany P588 FINISHED
Object IBM offices NE NERFINISHED

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: IBM offices | Statement: [Kista, hasMajorCompany, IBM offices]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: IBM offices
Context triple: [Kista, hasMajorCompany, IBM offices]
  • A. LinkedIn headquarters
    LinkedIn headquarters is the main corporate office of the professional networking platform LinkedIn, located in Sunnyvale, California.
  • B. IBM chosen
    IBM is a multinational technology and consulting company known for its pioneering work in computer hardware, software, and enterprise services.
  • C. World Office
    World Office is the central administrative office that coordinates the global activities and communications of the Friends World Committee for Consultation, the international Quaker organization.
  • D. Bristol-Myers Squibb offices
    Bristol-Myers Squibb offices in Plainsboro Township are part of the global pharmaceutical company's corporate and research facilities, supporting its drug development and business operations.
  • E. One Office
    One Office is an integrated organizational model used in the UN’s “Delivering as One” approach to streamline internal operations and support more coherent, efficient country-level work.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4a81bec8190b69adfdc1336a015 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6799161c48190825eca3027d1aa51 completed April 20, 2026, 7:08 p.m.
Created at: April 16, 2026, 11:29 a.m.