Triple

T8580537
Position Surface form Disambiguated ID Type / Status
Subject Frances Nelson E203162 entity
Predicate residence P75 FINISHED
Object Norfolk unclear NED1 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: Norfolk | Statement: [Frances Nelson, residence, Norfolk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norfolk
Context triple: [Frances Nelson, residence, Norfolk]
  • A. Norfolk
    Norfolk is a county in the East of England known for its rural landscapes, historic market towns, and extensive coastline along the North Sea.
  • B. Norfolk
    Norfolk is an independent coastal city in southeastern Virginia known for its major naval base and historic waterfront.
  • C. Portsmouth
    Portsmouth is a historic seaport city in southeastern New Hampshire known for its colonial-era architecture, maritime heritage, and vibrant cultural scene.
  • D. Portsmouth
    Portsmouth is a historic naval port city on England’s south coast, heavily targeted and damaged during the World War II Blitz.
  • E. Portsmouth
    Portsmouth is an independent port city in southeastern Virginia known for its historic shipyard, naval facilities, and waterfront along the Elizabeth River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69ca8328ebe481909a8c038fa79959b4 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbeb1a026c819089183f542eeb7837 completed March 31, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce89ae87f08190b83bc539e1d4eeaa completed April 2, 2026, 3:22 p.m.
Created at: March 30, 2026, 6:22 p.m.