Triple

T23892728
Position Surface form Disambiguated ID Type / Status
Subject Novara Calcio E600815 entity
Predicate notablePlayer P304 FINISHED
Object Riccardo Meggiorini
Riccardo Meggiorini is an Italian former professional footballer known as a hardworking forward who played for several Serie A and Serie B clubs during his career.
E2292130 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: Riccardo Meggiorini | Statement: [Novara Calcio, notablePlayer, Riccardo Meggiorini]
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: Riccardo Meggiorini
Triple: [Novara Calcio, notablePlayer, Riccardo Meggiorini]
Generated description
Riccardo Meggiorini is an Italian former professional footballer known as a hardworking forward who played for several Serie A and Serie B clubs during his career.

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_69e295341ac0819080647f2908af793c completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1cd050db8819090aa268ba7e5eeed completed April 29, 2026, 9:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5cc2abae3481909abdd7aa42290f9d completed July 19, 2026, 12:27 p.m.
NEDg Description generation batch_6a5cc5cbfa748190a12396026413df85 completed July 19, 2026, 12:40 p.m.
NED2 Entity disambiguation (via description) batch_6a5cc6c3b9dc81908efd4437f608edbc completed July 19, 2026, 12:44 p.m.
Created at: April 17, 2026, 8:25 p.m.