Triple

T1985302
Position Surface form Disambiguated ID Type / Status
Subject Tabula Bantina E43125 entity
Predicate associatedWithPlace P2830 FINISHED
Object Bantia E47124 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: Bantia | Statement: [Tabula Bantina, associatedWithPlace, Bantia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bantia
Context triple: [Tabula Bantina, associatedWithPlace, Bantia]
  • A. Bantia chosen
    Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
  • B. Bachok
    Bachok is a coastal town and district in the Malaysian state of Kelantan, known for its beaches and traditional Malay fishing villages.
  • C. Sitiawan
    Sitiawan is a coastal town in the Manjung District of Perak, Malaysia, known for its fishing industry and proximity to the port city of Lumut.
  • D. Batu Sawar
    Batu Sawar was a historically significant town in present-day Malaysia that served as an early political and administrative center of the Johor Sultanate after the fall of Malacca.
  • E. Kainan
    Kainan is a coastal city in central Wakayama Prefecture, Japan, known for its traditional industries and scenic seaside setting.
  • 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_69ae0ad53ccc8190b0e0f44cfddfe9a4 completed March 8, 2026, 11:48 p.m.
Created at: March 4, 2026, 7:37 p.m.