Triple

T13138804
Position Surface form Disambiguated ID Type / Status
Subject Vicky E312155 entity
Predicate hasFiancé P17846 FINISHED
Object Doug E1851 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: Doug | Statement: [Vicky, hasFiancé, Doug]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doug
Context triple: [Vicky, hasFiancé, Doug]
  • A. Doug chosen
    Doug is a common English masculine given name, typically used as a short form of Douglas.
  • B. Dave
    Dave is a common masculine given name, often a shortened form of David, used widely in English-speaking countries.
  • C. Don
    Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
  • D. Don
    Don is a classic 1978 Bollywood action-thriller film, starring Amitabh Bachchan in a dual role, that became iconic for its stylish crime narrative, memorable music, and enduring cultural impact.
  • E. Don
    The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d981b6a4348190b9922ed255759078 completed April 10, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e296e8e08190946a993a2b012204 completed May 3, 2026, 5:52 a.m.
Created at: April 9, 2026, 9:09 p.m.