Triple

T15380922
Position Surface form Disambiguated ID Type / Status
Subject Hildesheim district E367796 entity
Predicate contains P35 FINISHED
Object Giesen
Giesen is a municipality in Lower Saxony, Germany, located within the Hildesheim district.
E1164294 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: Giesen | Statement: [Hildesheim district, contains, Giesen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Giesen
Context triple: [Hildesheim district, contains, Giesen]
  • A. Geisenfeld
    Geisenfeld is a small town in Bavaria, Germany, known as the birthplace of prominent early Nazi politician Gregor Strasser.
  • B. Griesheim
    Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
  • C. Gieselau
    Gieselau is a small river in northern Germany that serves as a tributary of the Eider.
  • D. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • E. Ziegenhain
    Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
  • 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: Giesen
Triple: [Hildesheim district, contains, Giesen]
Generated description
Giesen is a municipality in Lower Saxony, Germany, located within the Hildesheim district.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Giesen
Target entity description: Giesen is a municipality in Lower Saxony, Germany, located within the Hildesheim district.
  • A. Geisenfeld
    Geisenfeld is a small town in Bavaria, Germany, known as the birthplace of prominent early Nazi politician Gregor Strasser.
  • B. Griesheim
    Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
  • C. Gieselau
    Gieselau is a small river in northern Germany that serves as a tributary of the Eider.
  • D. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • E. Ziegenhain
    Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
  • 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e61928c81908852c355d537ed9c completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c30ae4c8190b7a4739983963e86 completed May 9, 2026, 3:01 p.m.
NEDg Description generation batch_69ff4d8c7ccc8190baed00bfe77258e0 completed May 9, 2026, 3:06 p.m.
NED2 Entity disambiguation (via description) batch_69ff4df394f08190944378fe83094d15 completed May 9, 2026, 3:08 p.m.
Created at: April 10, 2026, 3:19 a.m.