Triple

T3327245
Position Surface form Disambiguated ID Type / Status
Subject John R. Rickford E69943 entity
Predicate hasAcademicAdvisor P167 FINISHED
Object William Labov E321180 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: William Labov | Statement: [John R. Rickford, hasAcademicAdvisor, William Labov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Labov
Context triple: [John R. Rickford, hasAcademicAdvisor, William Labov]
  • A. William Labov chosen
    William Labov is an American linguist regarded as a founder of modern sociolinguistics, known for his influential empirical studies of language variation and change in English.
  • B. Paul Kiparsky
    Paul Kiparsky is a prominent linguist known for his influential work in generative phonology and historical linguistics.
  • C. Michael Kenstowicz
    Michael Kenstowicz is an American linguist and phonologist known for his influential work on generative phonology and for co-authoring widely used textbooks in the field.
  • D. Dell Hymes
    Dell Hymes was an American linguist, anthropologist, and folklorist best known for founding the field of ethnography of communication and advancing sociolinguistics.
  • E. Martin Haspelmath
    Martin Haspelmath is a prominent German linguist known for his influential work in linguistic typology, grammatical description, and the development of cross-linguistic databases.
  • 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_69ad85a1829881908942c14075644d0d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb16f61248190bab10f4ac9e066f7 completed March 8, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a7ce34c81908df0c30a41fd925c completed March 12, 2026, 7:56 p.m.
Created at: March 8, 2026, 3:12 p.m.