Triple

T29216055
Position Surface form Disambiguated ID Type / Status
Subject Marko Jarić E740669 entity
Predicate playedFor P2170 FINISHED
Object Siena (Mens Sana Basket)
Siena (Mens Sana Basket) is an Italian professional basketball club, historically one of the country’s top teams and a regular competitor in European competitions.
E1855475 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: Siena (Mens Sana Basket) | Statement: [Marko Jarić, playedFor, Siena (Mens Sana Basket)]
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: Siena (Mens Sana Basket)
Triple: [Marko Jarić, playedFor, Siena (Mens Sana Basket)]
Generated description
Siena (Mens Sana Basket) is an Italian professional basketball club, historically one of the country’s top teams and a regular competitor in European competitions.

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_69f07cba2f808190a2746477d4e8345b completed April 28, 2026, 9:24 a.m.
NER Named-entity recognition batch_69f664099f388190a69b090d5ce32d18 completed May 2, 2026, 8:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2569cde77c81908a302f21a81e9646 completed June 7, 2026, 12:53 p.m.
NEDg Description generation batch_6a256e3f248c819090c3d806f3c3fd84 completed June 7, 2026, 1:12 p.m.
NED2 Entity disambiguation (via description) batch_6a2572394c84819085d3812520aeb050 completed June 7, 2026, 1:29 p.m.
Created at: April 28, 2026, 12:13 p.m.