Triple

T9568632
Position Surface form Disambiguated ID Type / Status
Subject Ann Petry E230854 entity
Predicate familyName P18 FINISHED
Object Lane E7099 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: Lane | Statement: [Ann Petry, familyName, Lane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lane
Context triple: [Ann Petry, familyName, Lane]
  • A. Lane chosen
    Lane is a common English surname borne by numerous notable individuals across fields such as science, politics, and the arts.
  • B. Jesus Lane
    Jesus Lane is a historic street in central Cambridge, England, known for its proximity to several colleges and notable university buildings.
  • C. Gillen Lane
    Gillen Lane is the fictional protagonist of the apocalyptic thriller film "The Omega Code," portrayed as a brilliant biblical prophecy scholar drawn into a global conspiracy.
  • D. Hosier Lane
    Hosier Lane is a famous laneway in Melbourne renowned for its ever-changing street art and graffiti-covered walls, making it a major attraction for urban art enthusiasts.
  • E. Laneast
    Laneast is a small rural village and civil parish in Cornwall, England, known for its historic church and traditional countryside setting.
  • 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_69ca847f22188190a56e4a97625bef22 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9987cb0c8190af32a1193de54890 completed April 1, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69d152b5b40c81909a84e34a944abfd0 completed April 4, 2026, 6:04 p.m.
Created at: March 30, 2026, 8:04 p.m.