Triple

T3336783
Position Surface form Disambiguated ID Type / Status
Subject Limmat E70156 entity
Predicate hasBridge P386 FINISHED
Object Lettensteg
Lettensteg is a pedestrian bridge spanning the Limmat River in Zurich, Switzerland, connecting paths along the former Letten railway viaduct.
E349665 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: Lettensteg | Statement: [Limmat, hasBridge, Lettensteg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lettensteg
Context triple: [Limmat, hasBridge, Lettensteg]
  • A. Bettlach
    Bettlach is a Swiss municipality located in the canton of Solothurn.
  • B. Oberengstringen
    Oberengstringen is a municipality in the canton of Zurich in Switzerland, located in the Limmat Valley near the city of Zurich.
  • C. Kreuzlingen
    Kreuzlingen is a Swiss town in the canton of Thurgau, located on the southern shore of Lake Constance near the German border.
  • D. Zuchwil
    Zuchwil is a Swiss municipality located near the city of Solothurn in the canton of Solothurn.
  • E. Oberegg
    Oberegg is a Swiss municipality in the canton of Appenzell Innerrhoden, known for its rural landscape and location in the Appenzell 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: Lettensteg
Triple: [Limmat, hasBridge, Lettensteg]
Generated description
Lettensteg is a pedestrian bridge spanning the Limmat River in Zurich, Switzerland, connecting paths along the former Letten railway viaduct.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lettensteg
Target entity description: Lettensteg is a pedestrian bridge spanning the Limmat River in Zurich, Switzerland, connecting paths along the former Letten railway viaduct.
  • A. Bettlach
    Bettlach is a Swiss municipality located in the canton of Solothurn.
  • B. Oberengstringen
    Oberengstringen is a municipality in the canton of Zurich in Switzerland, located in the Limmat Valley near the city of Zurich.
  • C. Kreuzlingen
    Kreuzlingen is a Swiss town in the canton of Thurgau, located on the southern shore of Lake Constance near the German border.
  • D. Zuchwil
    Zuchwil is a Swiss municipality located near the city of Solothurn in the canton of Solothurn.
  • E. Oberegg
    Oberegg is a Swiss municipality in the canton of Appenzell Innerrhoden, known for its rural landscape and location in the Appenzell 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bad97481909359e914d44a1a74 completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a8ad1a8819081d7ad2a48e2c5b9 completed March 12, 2026, 7:56 p.m.
NEDg Description generation batch_69b31c393f20819098d5761372d6a980 completed March 12, 2026, 8:04 p.m.
NED2 Entity disambiguation (via description) batch_69b3206be2748190874560701dc1ed18 completed March 12, 2026, 8:22 p.m.
Created at: March 8, 2026, 3:12 p.m.