Triple

T12877804
Position Surface form Disambiguated ID Type / Status
Subject Leipzig metropolitan region E308012 entity
Predicate containsCity P294 FINISHED
Object Bad Bibra
Bad Bibra is a small spa town in the Burgenlandkreis district of Saxony-Anhalt in central Germany, known for its rural setting and historical bathing tradition.
E1006463 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: Bad Bibra | Statement: [Leipzig metropolitan region, containsCity, Bad Bibra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Bibra
Context triple: [Leipzig metropolitan region, containsCity, Bad Bibra]
  • A. Kabale
    Kabale is a town in southwestern Uganda that serves as a key regional center and gateway to nearby attractions such as Bwindi Impenetrable National Park.
  • B. Bad Ragaz
    Bad Ragaz is a Swiss spa and resort town in the canton of St. Gallen, renowned for its thermal baths and alpine setting.
  • C. Bad Brambach
    Bad Brambach is a German spa town in the Vogtland region of Saxony, renowned for its mineral springs and therapeutic health resorts.
  • D. Bad Saarow
    Bad Saarow is a German spa town in Brandenburg known for its thermal baths and lakeside setting on the Scharmützelsee.
  • E. Bagirmi
    Bagirmi is a Central Sudanic language spoken primarily in southern Chad by the Bagirmi people.
  • 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: Bad Bibra
Triple: [Leipzig metropolitan region, containsCity, Bad Bibra]
Generated description
Bad Bibra is a small spa town in the Burgenlandkreis district of Saxony-Anhalt in central Germany, known for its rural setting and historical bathing tradition.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bad Bibra
Target entity description: Bad Bibra is a small spa town in the Burgenlandkreis district of Saxony-Anhalt in central Germany, known for its rural setting and historical bathing tradition.
  • A. Kabale
    Kabale is a town in southwestern Uganda that serves as a key regional center and gateway to nearby attractions such as Bwindi Impenetrable National Park.
  • B. Bad Ragaz
    Bad Ragaz is a Swiss spa and resort town in the canton of St. Gallen, renowned for its thermal baths and alpine setting.
  • C. Bad Brambach
    Bad Brambach is a German spa town in the Vogtland region of Saxony, renowned for its mineral springs and therapeutic health resorts.
  • D. Bad Saarow
    Bad Saarow is a German spa town in Brandenburg known for its thermal baths and lakeside setting on the Scharmützelsee.
  • E. Bagirmi
    Bagirmi is a Central Sudanic language spoken primarily in southern Chad by the Bagirmi people.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fa8474819086a8af3c90f3ca84 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69bb83bac8190838f7537b806317c completed May 3, 2026, 12:50 a.m.
NEDg Description generation batch_69f69cc6fa84819093a4317ab355f62b completed May 3, 2026, 12:54 a.m.
NED2 Entity disambiguation (via description) batch_69f69d845a9081909b40562825c1c500 completed May 3, 2026, 12:57 a.m.
Created at: April 9, 2026, 5:38 p.m.