Triple

T13192904
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Douglas, Countess of Morton E314036 entity
Predicate spouseFamilyName P49525 FINISHED
Object Douglas E282715 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: Douglas | Statement: [Elizabeth Douglas, Countess of Morton, spouseFamilyName, Douglas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Douglas
Context triple: [Elizabeth Douglas, Countess of Morton, spouseFamilyName, Douglas]
  • A. Douglas
    Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
  • B. Douglas
    Douglas is a narrow-gauge steam locomotive that operates on the historic Talyllyn Railway in Wales.
  • C. Douglas chosen
    Douglas is a town in South Lanarkshire, Scotland, historically known for its association with the powerful Douglas family and its medieval castle.
  • D. Douglas
    Douglas is a small rural community located within the township of Bonnechere Valley in eastern Ontario, Canada.
  • E. Douglas
    Douglas is a community area on the South Side of Chicago, Illinois, known for its historic residential neighborhoods and proximity to the city’s lakefront.
  • 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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c6158e4819082c8ad75b4dfdd90 completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff177ba88190afb2043cc157248d completed May 3, 2026, 7:53 a.m.
Created at: April 9, 2026, 9:16 p.m.