Triple

T4181443
Position Surface form Disambiguated ID Type / Status
Subject Halliburton E88203 entity
Predicate formerSubsidiary P6796 FINISHED
Object KBR E420034 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: KBR | Statement: [Halliburton, formerSubsidiary, KBR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KBR
Context triple: [Halliburton, formerSubsidiary, KBR]
  • A. KBR chosen
    KBR is a global engineering, construction, and services company known for major energy, infrastructure, and government contracting projects.
  • B. Koch Engineered Solutions
    Koch Engineered Solutions is an industrial technology and engineering company that provides process, pollution control, and optimization solutions across energy, chemical, and manufacturing sectors.
  • C. Halliburton
    Halliburton is a major American multinational corporation that provides products and services to the oil and gas industry worldwide.
  • D. Schlumberger
    Schlumberger is a leading global oilfield services company that provides technology, project management, and information solutions to the oil and gas industry.
  • E. Koch Industries
    Koch Industries is one of the largest privately held conglomerates in the United States, with diverse operations spanning energy, chemicals, manufacturing, and consumer products.
  • 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_69aed9477e8c81908bcb862d2db55b1d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0304702c8190899cbb0e3e41b987 completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5961845488190827b03e161f1235e completed March 14, 2026, 5:08 p.m.
Created at: March 9, 2026, 3:45 p.m.