Triple

T25146204
Position Surface form Disambiguated ID Type / Status
Subject Calahorra E629939 entity
Predicate isPartOf P10 FINISHED
Object Judicial district of Calahorra
The Judicial district of Calahorra is a Spanish judicial demarcation centered on the city of Calahorra that organizes and administers local courts and legal proceedings within its territorial scope.
E1668584 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: Judicial district of Calahorra | Statement: [Calahorra, isPartOf, Judicial district of Calahorra]
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: Judicial district of Calahorra
Triple: [Calahorra, isPartOf, Judicial district of Calahorra]
Generated description
The Judicial district of Calahorra is a Spanish judicial demarcation centered on the city of Calahorra that organizes and administers local courts and legal proceedings within its territorial scope.

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_69e2ff349e408190a6f4a5a66279f54d completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f4684c76048190bc6e4273d00aaceb completed May 1, 2026, 8:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105d06b3248190916843aa59dbcda6 completed May 22, 2026, 1:41 p.m.
NEDg Description generation batch_6a105e17b4708190bceee2e6c3f4f3a7 completed May 22, 2026, 1:45 p.m.
NED2 Entity disambiguation (via description) batch_6a105fa381408190b9343fb060d29374 completed May 22, 2026, 1:52 p.m.
Created at: April 18, 2026, 6:30 a.m.