Triple

T24849586
Position Surface form Disambiguated ID Type / Status
Subject Zürich-Höngg E621848 entity
Predicate partOf P40 FINISHED
Object Zürich Höngg–Wipkingen area
The Zürich Höngg–Wipkingen area is a district-level region in the city of Zürich, Switzerland, encompassing the neighborhoods of Höngg and Wipkingen along the Limmat River.
 E1660124 NE FINISHED

How this triple was built (2 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: Zürich Höngg–Wipkingen area | Statement: [Zürich-Höngg, partOf, Zürich Höngg–Wipkingen area]
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: Zürich Höngg–Wipkingen area
Triple: [Zürich-Höngg, partOf, Zürich Höngg–Wipkingen area]
Generated description
The Zürich Höngg–Wipkingen area is a district-level region in the city of Zürich, Switzerland, encompassing the neighborhoods of Höngg and Wipkingen along the Limmat River.

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_69e2fac297e481909d3aedc75f585e42 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f422d3d0308190b343e22170f080c3 completed May 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1033186ce081909ae0f5407b89a254 completed May 22, 2026, 10:42 a.m.
NEDg Description generation batch_6a1036e397a88190973cd7b91d567010 completed May 22, 2026, 10:58 a.m.
NED2 Entity disambiguation (via description) batch_6a10375a15888190851c33db7ff68814 completed May 22, 2026, 11 a.m.
Created at: April 18, 2026, 5:20 a.m.