Triple

T10382996
Position Surface form Disambiguated ID Type / Status
Subject Nathalie Emmanuel E244687 entity
Predicate playedCharacter P1507 FINISHED
Object Ramsey E241106 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: Ramsey | Statement: [Nathalie Emmanuel, playedCharacter, Ramsey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ramsey
Context triple: [Nathalie Emmanuel, playedCharacter, Ramsey]
  • A. Ramsey
    Ramsey is a coastal town in the north of the Isle of Man, known as one of the island’s main population centers and a local commercial and transport hub.
  • B. Ramsey chosen
    Ramsey is a brilliant hacker and tech expert in the Fast & Furious film series, known for creating the powerful surveillance program "God's Eye."
  • C. Ramsey
    Ramsey is a historic market town in the English county of Cambridgeshire, known for its medieval abbey and rural surroundings.
  • D. Ramsey
    Ramsey is a surname of English and Scottish origin borne by various notable individuals across fields such as science, politics, and the arts.
  • E. Gresham
    Gresham is a suburban city in the Portland metropolitan area of northwestern Oregon, known for its residential communities and proximity to outdoor recreation in the Columbia River Gorge.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9a2aafc8190aa11d14852fa1599 completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7959b6c2c819085b606280024c0f9 completed April 9, 2026, 12:03 p.m.
Created at: April 6, 2026, 12:04 p.m.