Triple

T1985237
Position Surface form Disambiguated ID Type / Status
Subject Sidicini E43123 entity
Predicate urbanCenter P749 FINISHED
Object Teanum Sidicinum E227805 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: Teanum Sidicinum | Statement: [Sidicini, urbanCenter, Teanum Sidicinum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teanum Sidicinum
Context triple: [Sidicini, urbanCenter, Teanum Sidicinum]
  • A. Teanum Sidicinum chosen
    Teanum Sidicinum was an important ancient city in Campania, Italy, serving as the chief urban center of the Sidicini people and later becoming a notable Roman municipality.
  • B. Hadrumetum
    Hadrumetum was an important ancient Phoenician and later Roman port city located on the coast of modern-day Tunisia.
  • C. Argentoratum
    Argentoratum is the ancient Roman military camp and settlement that later developed into the modern city of Strasbourg in northeastern France.
  • D. Aquincum
    Aquincum was an important ancient Roman military and civilian settlement located in what is now northern Budapest, Hungary.
  • E. Ariminum
    Ariminum was an important ancient Roman city on the Adriatic coast of Italy, known today as Rimini.
  • 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_69a88713ddc88190a969715658ebe7a8 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb821c2d48190abea6c89f37b51b1 completed March 7, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae2705752c81908054e8e0e426e86d completed March 9, 2026, 1:48 a.m.
Created at: March 4, 2026, 7:37 p.m.