Triple

T12888140
Position Surface form Disambiguated ID Type / Status
Subject Heringsdorf E308284 entity
Predicate hasPart P35 FINISHED
Object Bansin E275805 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: Bansin | Statement: [Heringsdorf, hasPart, Bansin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bansin
Context triple: [Heringsdorf, hasPart, Bansin]
  • A. Bansin chosen
    Bansin is a seaside resort town on Germany’s Baltic Sea coast, known as one of the “Kaiserbäder” (Imperial Spas) on the island of Usedom.
  • B. Bansha
    Bansha is a small rural village in County Tipperary, Ireland, known for its scenic setting near the Galtee Mountains and its traditional Irish community character.
  • C. Balaesang
    Balaesang is an Austronesian language of the Tomini–Tolitoli group spoken in Central Sulawesi, Indonesia.
  • D. Wansin
    Wansin is a village in the municipality of Hannut in the province of Liège, Belgium.
  • E. Balgüe
    Balgüe is a small rural village on Ometepe Island in Lake Nicaragua, known for its scenic setting near volcanic landscapes and eco-tourism lodges.
  • 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9714581988190afc720ffd7797860 completed April 10, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a5576ae4819084914697b2e86d9f completed May 3, 2026, 1:31 a.m.
Created at: April 9, 2026, 5:39 p.m.