Triple

T1102073
Position Surface form Disambiguated ID Type / Status
Subject University of Bologna E25401 entity
Predicate memberOf P10 FINISHED
Object Utrecht Network E26405 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: Utrecht Network | Statement: [University of Bologna, memberOf, Utrecht Network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Utrecht Network
Context triple: [University of Bologna, memberOf, Utrecht Network]
  • A. Utrecht Network chosen
    Utrecht Network is a European university network that promotes internationalization and academic cooperation among its member institutions through exchanges, joint projects, and shared initiatives.
  • B. Utrecht
    Utrecht is a historic city and province in the central Netherlands, known for its medieval old town, canals, and role as a religious and cultural center.
  • C. Eindhoven
    Eindhoven is a major city in the southern Netherlands known for its industrial and technological significance, particularly as a hub for electronics and design.
  • D. University of Harderwijk
    The University of Harderwijk was a former Dutch university known for training many 17th- and 18th-century scholars, physicians, and explorers.
  • E. Leiden
    Leiden is a historic Dutch city in South Holland known for its prestigious university, rich cultural heritage, and well-preserved canals and old town.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a49428d4448190b3b36991ceae87ce completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b9c21c2c8190a34d91a7afed23a9 completed March 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c47dbf88190a1898d7bda32ecb2 completed March 7, 2026, 4:03 p.m.
Created at: March 1, 2026, 7:43 p.m.