Triple

T13205029
Position Surface form Disambiguated ID Type / Status
Subject Old Town of Zurich E314337 entity
Predicate hasPart P35 FINISHED
Object Oberdorf
Oberdorf is a historic quarter within Zurich’s Old Town known for its narrow streets, traditional buildings, and lively mix of shops, restaurants, and cultural venues.
 E1027084 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: Oberdorf | Statement: [Old Town of Zurich, hasPart, Oberdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oberdorf
Context triple: [Old Town of Zurich, hasPart, Oberdorf]
  • A. Oberdorf
    Oberdorf is a Swiss municipality situated in the central alpine canton of Nidwalden.
  • B. Oberdorf
    Oberdorf is a locality within the Austrian municipality of Wolfurt in the state of Vorarlberg.
  • C. Oberaudorf
    Oberaudorf is a small Bavarian town in southern Germany near the Austrian border, known for its alpine scenery and ski tourism.
  • D. Oberägeri
    Oberägeri is a Swiss municipality in the canton of Zug, known for its scenic location by Lake Ägeri and surrounding pre-Alpine landscapes.
  • E. Oberweier
    Oberweier is a district of the town of Gaggenau in the Rastatt district of Baden-Württemberg, Germany, known for its village character within the Murg Valley region.
  • 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: Oberdorf
Triple: [Old Town of Zurich, hasPart, Oberdorf]
Generated description
Oberdorf is a historic quarter within Zurich’s Old Town known for its narrow streets, traditional buildings, and lively mix of shops, restaurants, and cultural venues.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oberdorf
Target entity description: Oberdorf is a historic quarter within Zurich’s Old Town known for its narrow streets, traditional buildings, and lively mix of shops, restaurants, and cultural venues.
  • A. Oberdorf
    Oberdorf is a Swiss municipality situated in the central alpine canton of Nidwalden.
  • B. Oberdorf
    Oberdorf is a locality within the Austrian municipality of Wolfurt in the state of Vorarlberg.
  • C. Oberaudorf
    Oberaudorf is a small Bavarian town in southern Germany near the Austrian border, known for its alpine scenery and ski tourism.
  • D. Oberägeri
    Oberägeri is a Swiss municipality in the canton of Zug, known for its scenic location by Lake Ägeri and surrounding pre-Alpine landscapes.
  • E. Oberweier
    Oberweier is a district of the town of Gaggenau in the Rastatt district of Baden-Württemberg, Germany, known for its village character within the Murg Valley region.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c9b0cf08190a1d71cc94139539d completed April 10, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f60eee288190bdb3ed6110394e48 completed May 3, 2026, 7:15 a.m.
NEDg Description generation batch_69f6f76ade3c8190b46655f104a1ceaa completed May 3, 2026, 7:21 a.m.
NED2 Entity disambiguation (via description) batch_69f6f85149cc8190adf68387475d3286 completed May 3, 2026, 7:25 a.m.
Created at: April 9, 2026, 9:17 p.m.