Triple

T5160582
Position Surface form Disambiguated ID Type / Status
Subject Tej Parker E116424 entity
Predicate worksWith P398 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: [Tej Parker, worksWith, Ramsey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ramsey
Context triple: [Tej Parker, worksWith, 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_69bd445edb3881909b93b34d260717fc completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79073a54819080cd1e8de6fe906a completed March 20, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed92b3ab48190900cf5c246dba433 completed March 21, 2026, 5:45 p.m.
Created at: March 20, 2026, 1:44 p.m.