Triple

T17737230
Position Surface form Disambiguated ID Type / Status
Subject Victor Marie du Pont E442751 entity
Predicate affiliation P10 FINISHED
Object du Pont company 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: du Pont company | Statement: [Victor Marie du Pont, affiliation, du Pont company]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: du Pont company
Context triple: [Victor Marie du Pont, affiliation, du Pont company]
  • A. Du Pont
    Du Pont is a prominent American industrial and philanthropic family best known for founding the chemical company E.I. du Pont de Nemours and Company.
  • B. Dupont
    Dupont is a common French surname shared by various notable individuals across fields such as politics, arts, and sports.
  • C. DuPont chosen
    DuPont is a major American chemical company historically known for pioneering materials science innovations and playing a key role in U.S. industrial and wartime production.
  • D. Rohm and Haas
    Rohm and Haas is a specialty chemicals company known for producing advanced materials and chemical products used in coatings, electronics, and industrial applications.
  • E. DowDuPont
    DowDuPont was a large American chemical conglomerate formed by the merger of Dow Chemical and DuPont, later split into three independent companies focused on agriculture, materials science, and specialty products.
  • 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e478ec48988190a503f9aafeab6d23 completed April 19, 2026, 6:40 a.m.
Created at: April 10, 2026, 10:09 a.m.