Triple

T6649691
Position Surface form Disambiguated ID Type / Status
Subject Juventus Women E150788 entity
Predicate homeStadiumCity P5282 FINISHED
Object Vinovo
Vinovo is a municipality in Italy’s Piedmont region, located near Turin and known for hosting Juventus’ training facilities and women’s team matches.
 E609733 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: Vinovo | Statement: [Juventus Women, homeStadiumCity, Vinovo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vinovo
Context triple: [Juventus Women, homeStadiumCity, Vinovo]
  • A. Odintsovo
    Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
  • B. Zvenigorod
    Zvenigorod is a historic town near Moscow, Russia, known for its ancient monasteries, traditional Russian architecture, and role as a cultural and spiritual center.
  • C. Konakovo
    Konakovo is a town in Tver Oblast, Russia, situated on the Volga River and known for its power station and riverside recreation.
  • D. Astapovo
    Astapovo is a small Russian railway station village historically known as the place where the writer Leo Tolstoy died in 1910.
  • E. Safonovo
    Safonovo is a small industrial town in western Russia known for its role in the regional energy and manufacturing sectors within Smolensk Oblast.
  • 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: Vinovo
Triple: [Juventus Women, homeStadiumCity, Vinovo]
Generated description
Vinovo is a municipality in Italy’s Piedmont region, located near Turin and known for hosting Juventus’ training facilities and women’s team matches.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vinovo
Target entity description: Vinovo is a municipality in Italy’s Piedmont region, located near Turin and known for hosting Juventus’ training facilities and women’s team matches.
  • A. Odintsovo
    Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
  • B. Zvenigorod
    Zvenigorod is a historic town near Moscow, Russia, known for its ancient monasteries, traditional Russian architecture, and role as a cultural and spiritual center.
  • C. Konakovo
    Konakovo is a town in Tver Oblast, Russia, situated on the Volga River and known for its power station and riverside recreation.
  • D. Astapovo
    Astapovo is a small Russian railway station village historically known as the place where the writer Leo Tolstoy died in 1910.
  • E. Safonovo
    Safonovo is a small industrial town in western Russia known for its role in the regional energy and manufacturing sectors within Smolensk Oblast.
  • 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_69c687f2c9508190a60b9aad31d3f358 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b04408508190a87a669b32364368 completed March 27, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eef91eb08190a00ae027c21b08bf completed March 27, 2026, 8:56 p.m.
NEDg Description generation batch_69c6f1ed97248190ab2253b3b2457f4f completed March 27, 2026, 9:09 p.m.
NED2 Entity disambiguation (via description) batch_69c6f2c18c0081908958b7ffeed7a787 completed March 27, 2026, 9:12 p.m.
Created at: March 27, 2026, 2:01 p.m.