Triple

T6321970
Position Surface form Disambiguated ID Type / Status
Subject Paul Webb E141763 entity
Predicate work P12692 FINISHED
Object Selma unclear NED1 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: Selma | Statement: [Paul Webb, work, Selma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Selma
Context triple: [Paul Webb, work, Selma]
  • A. Selma
    Selma is a feminine given name of Scandinavian origin, notably borne by the Swedish author and Nobel laureate Selma Lagerlöf.
  • B. Selma
    Selma is a historic city in central Alabama best known as a key site of the American civil rights movement, particularly the 1965 Selma-to-Montgomery marches.
  • C. Selma
    Selma is a small agricultural city in California’s San Joaquin Valley, known for its raisin production and location within Fresno County.
  • D. Selma
    Selma is a small suburban city in the San Antonio metropolitan area of south-central Texas, known for its residential communities and proximity to major regional highways and attractions.
  • E. Selma (2014 film)
    Selma is a 2014 historical drama film that chronicles Martin Luther King Jr.'s leadership in the 1965 voting rights marches from Selma to Montgomery, Alabama.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69c008d13b8c8190be47d896eb735605 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c064c76dfc8190a1d44fd0c4402a0e completed March 22, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6040b1e0481908095decce40107b4 completed March 27, 2026, 4:14 a.m.
Created at: March 22, 2026, 4:29 p.m.