Triple

T9814771
Position Surface form Disambiguated ID Type / Status
Subject Ingelheim am Rhein E238373 entity
Predicate hasPart P35 FINISHED
Object Sporkenheim
Sporkenheim is a district or locality within the town of Ingelheim am Rhein in Rhineland-Palatinate, Germany.
E874898 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: Sporkenheim | Statement: [Ingelheim am Rhein, hasPart, Sporkenheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sporkenheim
Context triple: [Ingelheim am Rhein, hasPart, Sporkenheim]
  • A. Poppenhausen
    Poppenhausen is a small German town located in the Schweinfurt administrative region of northern Bavaria.
  • B. Passenheim
    Passenheim is the former German name of the town now known as Pasym, located in northeastern Poland’s historic region of Masuria.
  • C. Blaubeuren
    Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
  • D. Badenweiler
    Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
  • E. Sulzheim
    Sulzheim is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
  • 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: Sporkenheim
Triple: [Ingelheim am Rhein, hasPart, Sporkenheim]
Generated description
Sporkenheim is a district or locality within the town of Ingelheim am Rhein in Rhineland-Palatinate, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sporkenheim
Target entity description: Sporkenheim is a district or locality within the town of Ingelheim am Rhein in Rhineland-Palatinate, Germany.
  • A. Poppenhausen
    Poppenhausen is a small German town located in the Schweinfurt administrative region of northern Bavaria.
  • B. Passenheim
    Passenheim is the former German name of the town now known as Pasym, located in northeastern Poland’s historic region of Masuria.
  • C. Blaubeuren
    Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
  • D. Badenweiler
    Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
  • E. Sulzheim
    Sulzheim is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
  • 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb2f19660819083e3f15780352052 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d95e38789881909e45e8d0b0489a59 completed April 10, 2026, 8:31 p.m.
NEDg Description generation batch_69d95f508b6481909405f0404246c69e completed April 10, 2026, 8:36 p.m.
NED2 Entity disambiguation (via description) batch_69d9600a29808190af583d2fd696ec6a completed April 10, 2026, 8:39 p.m.
Created at: March 30, 2026, 8:30 p.m.