Triple

T13518087
Position Surface form Disambiguated ID Type / Status
Subject Rosa Hubermann E322819 entity
Predicate residesIn P75 FINISHED
Object Himmel Street E1056114 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: Himmel Street | Statement: [Rosa Hubermann, residesIn, Himmel Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Himmel Street
Context triple: [Rosa Hubermann, residesIn, Himmel Street]
  • A. Himmel Street chosen
    Himmel Street is the fictional working-class German street in the town of Molching where much of Markus Zusak’s novel "The Book Thief" takes place.
  • B. Love Street
    Love Street was a historic football stadium in Paisley, Scotland, best known as the long-time home of St Mirren F.C.
  • C. Grey Street
    Grey Street is a renowned historic thoroughfare in Newcastle upon Tyne, celebrated for its elegant Georgian architecture and cultural significance.
  • 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. Stone Street
    Stone Street is a historic cobblestone street in Lower Manhattan’s Financial District, known for its preserved 17th-century character and popular outdoor dining scene.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa27f048190bed33a98e28c8d09 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7b05c844c8190bb4b72d2400a6355 completed May 3, 2026, 8:30 p.m.
Created at: April 9, 2026, 9:44 p.m.