Triple

T9684343
Position Surface form Disambiguated ID Type / Status
Subject Glâne District E234366 entity
Predicate containsMunicipality P852 FINISHED
Object Billens-Hennens
Billens-Hennens is a small municipality in the canton of Fribourg in western Switzerland, known for its rural character and location within the Glâne District.
E815270 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: Billens-Hennens | Statement: [Glâne District, containsMunicipality, Billens-Hennens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Billens-Hennens
Context triple: [Glâne District, containsMunicipality, Billens-Hennens]
  • A. Langhans
    Langhans is a German surname most notably associated with Carl Gotthard Langhans, the architect of Berlin’s Brandenburg Gate.
  • B. Hohberg
    Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
  • C. Helleren
    Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
  • D. Braunshardt
    Braunshardt is a district of the town of Weiterstadt in the state of Hesse, Germany.
  • E. Wolthusen
    Wolthusen is a district of the seaport city of Emden in Lower Saxony, Germany, known for its residential character and proximity to the Ems estuary.
  • 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: Billens-Hennens
Triple: [Glâne District, containsMunicipality, Billens-Hennens]
Generated description
Billens-Hennens is a small municipality in the canton of Fribourg in western Switzerland, known for its rural character and location within the Glâne District.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Billens-Hennens
Target entity description: Billens-Hennens is a small municipality in the canton of Fribourg in western Switzerland, known for its rural character and location within the Glâne District.
  • A. Langhans
    Langhans is a German surname most notably associated with Carl Gotthard Langhans, the architect of Berlin’s Brandenburg Gate.
  • B. Hohberg
    Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
  • C. Helleren
    Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
  • D. Braunshardt
    Braunshardt is a district of the town of Weiterstadt in the state of Hesse, Germany.
  • E. Wolthusen
    Wolthusen is a district of the seaport city of Emden in Lower Saxony, Germany, known for its residential character and proximity to the Ems estuary.
  • 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_69ca84c99e34819092e5563a7106cfca completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9ccf21a08190a1302b933b9e50be completed April 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19106e67881909505287620d2f781 completed April 4, 2026, 10:30 p.m.
NEDg Description generation batch_69d19375fd8481909620e8e68d73ec17 completed April 4, 2026, 10:40 p.m.
NED2 Entity disambiguation (via description) batch_69d19416efd48190865d0178e5e893fa completed April 4, 2026, 10:43 p.m.
Created at: March 30, 2026, 8:16 p.m.