Triple

T21205262
Position Surface form Disambiguated ID Type / Status
Subject Bad Iburg E522559 entity
Predicate hasSubdivision P747 FINISHED
Object Sentrup
Sentrup is a locality within the town of Bad Iburg in Lower Saxony, Germany.
E1472050 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: Sentrup | Statement: [Bad Iburg, hasSubdivision, Sentrup]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sentrup
Context triple: [Bad Iburg, hasSubdivision, Sentrup]
  • A. Lauterbourg
    Lauterbourg is a small French town in the Alsace region near the German border, known for its cross-border role within the Upper Rhine area and its historic Rhine river setting.
  • B. Dyhernfurth
    Dyhernfurth was a town in Lower Silesia (now Brzeg Dolny, Poland) that became known for its chemical industry, including facilities associated with German chemist Otto Ambros during World War II.
  • C. Dehéries
    Dehéries is a small commune in the Nord department of northern France.
  • D. Hungen
    Hungen is a small town in the German state of Hesse, known for its historic town center and rural surroundings.
  • E. Heimirich
    Heimirich is a Germanic given name of ancient origin, from which the modern name Heinrich is derived.
  • 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: Sentrup
Triple: [Bad Iburg, hasSubdivision, Sentrup]
Generated description
Sentrup is a locality within the town of Bad Iburg in Lower Saxony, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sentrup
Target entity description: Sentrup is a locality within the town of Bad Iburg in Lower Saxony, Germany.
  • A. Lauterbourg
    Lauterbourg is a small French town in the Alsace region near the German border, known for its cross-border role within the Upper Rhine area and its historic Rhine river setting.
  • B. Dyhernfurth
    Dyhernfurth was a town in Lower Silesia (now Brzeg Dolny, Poland) that became known for its chemical industry, including facilities associated with German chemist Otto Ambros during World War II.
  • C. Dehéries
    Dehéries is a small commune in the Nord department of northern France.
  • D. Hungen
    Hungen is a small town in the German state of Hesse, known for its historic town center and rural surroundings.
  • E. Heimirich
    Heimirich is a Germanic given name of ancient origin, from which the modern name Heinrich is derived.
  • 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_69e0b5112d8881909510b2dcdc93106d completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e734342e9081909e241bed54dbc0b4 completed April 21, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a097ed0fc988190b112058f5bb03515 completed May 17, 2026, 8:39 a.m.
NEDg Description generation batch_6a09807f39188190adaba95201b15d49 completed May 17, 2026, 8:46 a.m.
NED2 Entity disambiguation (via description) batch_6a0981288c4c8190bc9ecf6073be5ab3 completed May 17, 2026, 8:49 a.m.
Created at: April 16, 2026, 3:20 p.m.