Triple

T19933527
Position Surface form Disambiguated ID Type / Status
Subject Michael Balint E479115 entity
Predicate movedTo P195 FINISHED
Object Manchester NE NERFINISHED

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: Manchester | Statement: [Michael Balint, movedTo, Manchester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manchester
Context triple: [Michael Balint, movedTo, Manchester]
  • A. Manchester chosen
    Manchester is a major city in northwest England known for its industrial heritage, vibrant cultural scene, and influential contributions to music, sport, and science.
  • B. Manchester
    Manchester is the most populous city in the U.S. state of New Hampshire and a major economic and cultural center for the region.
  • C. Manchester
    Manchester is a historic neighborhood on Pittsburgh’s North Side known for its 19th-century architecture and designation as a historic district.
  • D. Manchester
    Manchester is a suburban town in central Connecticut known for its historic mills, shopping districts, and residential communities within the Greater Hartford area.
  • E. Manchester
    Manchester is a common English surname, notably borne by American singer and songwriter Melissa Manchester.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e521855c8190b41871700afc8d6a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65a1553348190a6c4004d3f9a57c5 completed April 20, 2026, 4:53 p.m.
Created at: April 10, 2026, 1:53 p.m.