Triple

T3014899
Position Surface form Disambiguated ID Type / Status
Subject Schlieren E82313 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Weiningen
Weiningen is a small Swiss municipality in the canton of Zurich, located in the Limmat Valley near the city of Zurich.
E325834 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: Weiningen | Statement: [Schlieren, neighboringMunicipality, Weiningen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weiningen
Context triple: [Schlieren, neighboringMunicipality, Weiningen]
  • A. Oensingen
    Oensingen is a Swiss municipality located in the canton of Solothurn, known as a regional transport hub near the Jura mountains.
  • B. Leichlingen
    Leichlingen is a small town in North Rhine-Westphalia, Germany, known for its scenic location along the Wupper River and its fruit-growing traditions.
  • C. Nellingen
    Nellingen is a small municipality in the Alb-Donau district of the German state of Baden-Württemberg, situated on the Swabian Jura plateau.
  • D. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • E. Enzweihingen
    Enzweihingen is a village in the German state of Baden-Württemberg, known historically as the place where former Nazi foreign minister Konstantin von Neurath died.
  • 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: Weiningen
Triple: [Schlieren, neighboringMunicipality, Weiningen]
Generated description
Weiningen is a small Swiss municipality in the canton of Zurich, located in the Limmat Valley near the city of Zurich.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Weiningen
Target entity description: Weiningen is a small Swiss municipality in the canton of Zurich, located in the Limmat Valley near the city of Zurich.
  • A. Oensingen
    Oensingen is a Swiss municipality located in the canton of Solothurn, known as a regional transport hub near the Jura mountains.
  • B. Leichlingen
    Leichlingen is a small town in North Rhine-Westphalia, Germany, known for its scenic location along the Wupper River and its fruit-growing traditions.
  • C. Nellingen
    Nellingen is a small municipality in the Alb-Donau district of the German state of Baden-Württemberg, situated on the Swabian Jura plateau.
  • D. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • E. Enzweihingen
    Enzweihingen is a village in the German state of Baden-Württemberg, known historically as the place where former Nazi foreign minister Konstantin von Neurath died.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a69e8148190a97507740c9d26a8 completed March 8, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f8663fb881909d7c179f4f61d313 completed March 11, 2026, 11:19 p.m.
NEDg Description generation batch_69b1f9608e88819098f4044e54e0d908 completed March 11, 2026, 11:23 p.m.
NED2 Entity disambiguation (via description) batch_69b1fe3c8f408190988e7c7e3a51057e completed March 11, 2026, 11:43 p.m.
Created at: March 8, 2026, 3 p.m.