Triple

T16147505
Position Surface form Disambiguated ID Type / Status
Subject Damien Timmer E391822 entity
Predicate notableWork P4 FINISHED
Object Monroe E974063 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: Monroe | Statement: [Damien Timmer, notableWork, Monroe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monroe
Context triple: [Damien Timmer, notableWork, Monroe]
  • A. Monroe
    Monroe is a Chicago 'L' rapid transit station located in the Loop and served by the Chicago Transit Authority's Red Line.
  • B. Monroe
    Monroe is a surname most famously associated with Earl Monroe, a Hall of Fame American basketball player known for his flashy playing style.
  • C. Monroe
    Monroe is a city in southeastern Michigan known for its location along the River Raisin and its historical significance in the War of 1812.
  • D. Monroe
    Monroe is a given name used as a first name, notably borne by actor Jackson Rathbone.
  • E. Monroe chosen
    Monroe is a British medical drama television series centered on a brilliant but troubled neurosurgeon, starring James Nesbitt in the title role.
  • 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_69d87f1c65e48190aa2b4c472e9bafc4 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21d947e68819081b4b7c757ce71b6 completed April 17, 2026, 11:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7a7dc3481909f933acd72d6feff completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:01 a.m.