Triple

T2845131
Position Surface form Disambiguated ID Type / Status
Subject Reichsgau Wartheland E62564 entity
Predicate containsCity P294 FINISHED
Object Turek
Turek is a town in central Poland known historically for its textile industry and its location in the Greater Poland region.
E304119 NE FINISHED

How this triple was built (4 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: Turek | Statement: [Reichsgau Wartheland, containsCity, Turek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turek
Context triple: [Reichsgau Wartheland, containsCity, Turek]
  • A. Tachov
    Tachov is a town in western Czechia that serves as an administrative center and local hub within the Plzeň Region.
  • B. Trebsen
    Trebsen is a small town in the Free State of Saxony in eastern Germany, known for its historic castle and location along the Mulde River.
  • C. Jastarnia
    Jastarnia is a seaside resort town and fishing port on Poland’s Baltic coast, popular for its beaches and water sports.
  • D. Olecko
    Olecko is a small town in northeastern Poland known for its lakeside setting and location within the historic region of Masuria.
  • E. Łuck
    Łuck is the Polish name for Lutsk, a historic city in western Ukraine known for its medieval castle and role as a regional cultural center.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Turek
Triple: [Reichsgau Wartheland, containsCity, Turek]
Generated description
Turek is a town in central Poland known historically for its textile industry and its location in the Greater Poland region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Turek
Target entity description: Turek is a town in central Poland known historically for its textile industry and its location in the Greater Poland region.
  • A. Tachov
    Tachov is a town in western Czechia that serves as an administrative center and local hub within the Plzeň Region.
  • B. Trebsen
    Trebsen is a small town in the Free State of Saxony in eastern Germany, known for its historic castle and location along the Mulde River.
  • C. Jastarnia
    Jastarnia is a seaside resort town and fishing port on Poland’s Baltic coast, popular for its beaches and water sports.
  • D. Olecko
    Olecko is a small town in northeastern Poland known for its lakeside setting and location within the historic region of Masuria.
  • E. Łuck
    Łuck is the Polish name for Lutsk, a historic city in western Ukraine known for its medieval castle and role as a regional cultural center.
  • F. None of above. chosen

Provenance (5 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_69ab4c3d16bc81908b3a1c98fbd287fe completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf1b58c88190b45d8c5a76dc52ac completed March 7, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8d850b481909850ff5e89021824 completed March 10, 2026, 9:48 a.m.
NEDg Description generation batch_69afe990ce088190b42b20037c1eef3f completed March 10, 2026, 9:51 a.m.
NED2 Entity disambiguation (via description) batch_69b00d04f42081909d59e1ad1bec6c34 completed March 10, 2026, 12:22 p.m.
Created at: March 6, 2026, 10:02 p.m.