Triple

T4480160
Position Surface form Disambiguated ID Type / Status
Subject Battle of Emsdorf E100110 entity
Predicate belligerent P375 FINISHED
Object Hanover E21642 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: Hanover | Statement: [Battle of Emsdorf, belligerent, Hanover]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanover
Context triple: [Battle of Emsdorf, belligerent, Hanover]
  • A. Hanover chosen
    Hanover is a historic city in northern Germany that served as the capital of the former Kingdom of Hanover and the ancestral seat of the British House of Hanover.
  • B. Hanover
    Hanover is a small New Hampshire town best known as the home of Dartmouth College, an Ivy League institution.
  • C. Hanover
    Hanover is a small suburban town in Plymouth County, Massachusetts, known for its residential character and local businesses south of Boston.
  • D. Hamburg
    Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
  • E. Braunschweig
    Braunschweig is a historic city in northern Germany known for its medieval architecture, cultural institutions, and role as an important economic and scientific center.
  • 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_69b34553cbe48190afa8ac1cac285b86 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b356dcaba88190ae2d64c038450ca6 completed March 13, 2026, 12:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69b627a72da881908e1a4965177727eb completed March 15, 2026, 3:29 a.m.
Created at: March 12, 2026, 11:36 p.m.