Triple

T3597039
Position Surface form Disambiguated ID Type / Status
Subject Harold Prince E76164 entity
Predicate placeOfDeath P21 FINISHED
Object Reykjavík E28255 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: Reykjavík | Statement: [Harold Prince, placeOfDeath, Reykjavík]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reykjavík
Context triple: [Harold Prince, placeOfDeath, Reykjavík]
  • A. Reykjavík, Iceland chosen
    Reykjavík, Iceland is the capital and largest city of Iceland, known for its vibrant cultural scene, geothermal pools, and role as the country’s political and economic center.
  • B. Hafnarfjörður
    Hafnarfjörður is a port town in southwestern Iceland known for its lava-field setting, fishing industry, and role as part of the Reykjavík metropolitan area.
  • C. Tórshavn
    Tórshavn is the capital and largest city of the Faroe Islands, serving as the political, cultural, and economic center of the archipelago.
  • D. Garðabær
    Garðabær is a suburban municipality in the Capital Region of Iceland, known for being part of the greater Reykjavík area and hosting some of the country’s prominent residential neighborhoods.
  • E. Copenhagen
    Copenhagen is the capital and largest city of Denmark, known for its historic architecture, vibrant cultural scene, and high quality of life.
  • 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_69ad85d8042081908af94a04c410dec0 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc19b26bc8190b3cc0613a1a98361 completed March 8, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b403130cf081909bb90800d7dc2d6f completed March 13, 2026, 12:29 p.m.
Created at: March 8, 2026, 3:22 p.m.