Triple

T19315361
Position Surface form Disambiguated ID Type / Status
Subject Secretary of the Democrats of the Left E483083 entity
Predicate officeHolder P537 FINISHED
Object Gavino Angius
Gavino Angius is an Italian politician known for his prominent leadership role within the center-left Democrats of the Left party.
E1995950 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: Gavino Angius | Statement: [Secretary of the Democrats of the Left, officeHolder, Gavino Angius]
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: Gavino Angius
Triple: [Secretary of the Democrats of the Left, officeHolder, Gavino Angius]
Generated description
Gavino Angius is an Italian politician known for his prominent leadership role within the center-left Democrats of the Left party.

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_69d8e8d04d5c8190baa816986f2b1d1e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e60d833034819092a8414d5e0fc26e completed April 20, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0ba602a881909d21bccb6d52b7ee completed June 14, 2026, 8:14 p.m.
NEDg Description generation batch_6a2f0c75144c8190bd305d2b1c10a6e3 completed June 14, 2026, 8:17 p.m.
NED2 Entity disambiguation (via description) batch_6a2f2edbc2f0819097f1dcfafe9e442c completed June 14, 2026, 10:44 p.m.
Created at: April 10, 2026, 1:32 p.m.