Triple

T7279270
Position Surface form Disambiguated ID Type / Status
Subject AMD EPYC E163106 entity
Predicate codename P2980 FINISHED
Object Bergamo E210593 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: Bergamo | Statement: [AMD EPYC, codename, Bergamo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bergamo
Context triple: [AMD EPYC, codename, Bergamo]
  • A. Bergamo chosen
    Bergamo is a historic city in northern Italy known for its medieval walled upper town, rich artistic heritage, and strategic location at the foothills of the Alps.
  • B. Brescia
    Brescia is a historic industrial and cultural city in northern Italy, known for its Roman and medieval architecture and its role as an economic hub.
  • C. Legnano
    Legnano is a town in the Lombardy region of northern Italy, historically known for its medieval Battle of Legnano and its industrial development.
  • D. Busto Arsizio
    Busto Arsizio is an industrial city in the Lombardy region of northern Italy, known for its textile and manufacturing heritage and its location within the greater Milan metropolitan area.
  • E. Varese
    Varese is a city in northern Italy known for its lakeside setting, surrounding Prealps, and role as an important economic and cultural center in the Lombardy region.
  • 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_69c6885c5964819085b209701769877f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb3251808190bd9da71bc183c945 completed March 27, 2026, 8:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c861296e5c8190aa2a189e71963de9 completed March 28, 2026, 11:15 p.m.
Created at: March 27, 2026, 2:59 p.m.