Triple

T8764681
Position Surface form Disambiguated ID Type / Status
Subject Daniel Caesar E208307 entity
Predicate givenName P17 FINISHED
Object Ashton E236180 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: Ashton | Statement: [Daniel Caesar, givenName, Ashton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ashton
Context triple: [Daniel Caesar, givenName, Ashton]
  • A. Ashton chosen
    Ashton is a masculine given name of English origin that has become well known through figures such as actor and entrepreneur Ashton Kutcher.
  • B. Ashton
    Ashton is a small coastal town on Union Island in Saint Vincent and the Grenadines, known as one of the island’s main settlements.
  • C. Ashton
    Ashton is a small village in the town of Cumberland in Providence County, Rhode Island, known for its historic mill district along the Blackstone River.
  • D. Ashton
    Ashton is a small town in South Africa’s Western Cape, known for its fruit farming and position along the scenic Route 62.
  • E. Arniston
    Arniston is a historic Scottish country estate in Midlothian, long associated with the influential Dundas family.
  • 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_69ca835df7e08190ac875664cca8f9ca completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5dfdef9881908a7f079d87e8e338 completed March 31, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf436106708190aedba29e57445303 completed April 3, 2026, 4:34 a.m.
Created at: March 30, 2026, 6:40 p.m.