Triple

T228681
Position Surface form Disambiguated ID Type / Status
Subject Lower Saxony E4364 entity
Predicate containsCity P294 FINISHED
Object Celle
Celle is a historic town in northern Germany renowned for its well-preserved half-timbered old town and ducal palace.
 E30373 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: Celle | Statement: [Lower Saxony, containsCity, Celle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Celle
Context triple: [Lower Saxony, containsCity, Celle]
  • A. Rednitz
    The Rednitz is a river in Bavaria, Germany, that flows through cities such as Fürth and joins with the Pegnitz to form the Regnitz.
  • B. Mouton
    Mouton is an academic publishing house known for its influential works in linguistics and related fields.
  • C. Escharen
    Escharen is a village in the Dutch province of North Brabant that was formerly an independent municipality before being incorporated into a larger administrative unit.
  • D. Ornytion
    Ornytion is a minor figure in Greek mythology, traditionally known as a son of the Corinthian king Sisyphus and father of Merope.
  • E. Tulle
    Tulle is a historic town in central France, known as the capital of the Corrèze department in the Nouvelle-Aquitaine 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: Celle
Triple: [Lower Saxony, containsCity, Celle]
Generated description
Celle is a historic town in northern Germany renowned for its well-preserved half-timbered old town and ducal palace.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Celle
Target entity description: Celle is a historic town in northern Germany renowned for its well-preserved half-timbered old town and ducal palace.
  • A. Rednitz
    The Rednitz is a river in Bavaria, Germany, that flows through cities such as Fürth and joins with the Pegnitz to form the Regnitz.
  • B. Mouton
    Mouton is an academic publishing house known for its influential works in linguistics and related fields.
  • C. Escharen
    Escharen is a village in the Dutch province of North Brabant that was formerly an independent municipality before being incorporated into a larger administrative unit.
  • D. Ornytion
    Ornytion is a minor figure in Greek mythology, traditionally known as a son of the Corinthian king Sisyphus and father of Merope.
  • E. Tulle
    Tulle is a historic town in central France, known as the capital of the Corrèze department in the Nouvelle-Aquitaine 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_69a257363ffc81909757bde7ab3404da completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c9140c48190b90647400854b37e completed Feb. 28, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3673257f081908bcb84cbedef3c07 completed Feb. 28, 2026, 10:07 p.m.
NEDg Description generation batch_69a367b28e6c819082ad23cad05c5071 completed Feb. 28, 2026, 10:09 p.m.
NED2 Entity disambiguation (via description) batch_69a3683fafec8190b46278c7309fe577 completed Feb. 28, 2026, 10:12 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.