Triple

T5934134
Position Surface form Disambiguated ID Type / Status
Subject ArcelorMittal E132002 entity
Predicate hasDivision P35 FINISHED
Object ArcelorMittal Brazil E132002 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: ArcelorMittal Brazil | Statement: [ArcelorMittal, hasDivision, ArcelorMittal Brazil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ArcelorMittal Brazil
Context triple: [ArcelorMittal, hasDivision, ArcelorMittal Brazil]
  • A. ArcelorMittal chosen
    ArcelorMittal is a multinational steel manufacturing corporation and one of the world’s largest steel producers, headquartered in Luxembourg.
  • B. Siderúrgicos
    Siderúrgicos is the nickname of Chilean football club Huachipato, reflecting the region’s strong steel industry heritage.
  • C. Dofasco
    Dofasco is a major Canadian steel manufacturer based in Hamilton, Ontario, long recognized as one of the city’s most prominent industrial employers.
  • D. SEVERSTAL
    SEVERSTAL is the radio callsign used by Severstal Aircompany, a Russian airline.
  • E. Fundidora de Fierro y Acero de Monterrey
    Fundidora de Fierro y Acero de Monterrey was a major Mexican iron and steel foundry in Monterrey that played a key role in the country’s early industrialization.
  • 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_69c0085c55dc8190aa90e242c956e2fa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c038a0c4e481908170d615330edb1a completed March 22, 2026, 6:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c069e450819096b268637ffcd219 completed March 23, 2026, 4:24 a.m.
Created at: March 22, 2026, 4 p.m.