Triple

T1430360
Position Surface form Disambiguated ID Type / Status
Subject 1st Infantry Division E30429 entity
Predicate worldWarIITheatre P710 FINISHED
Object Italy E863 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: Italy | Statement: [1st Infantry Division, worldWarIITheatre, Italy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Italy
Context triple: [1st Infantry Division, worldWarIITheatre, Italy]
  • A. Italy chosen
    Italy is a Southern European country known for its influential history, art, cuisine, and role as a founding member of the European Union.
  • B. Italo
    Italo is a masculine Italian given name historically borne by notable figures in politics, aviation, literature, and the arts.
  • C. ITA
    ITA is a U.S. government agency within the Department of Commerce that promotes American exports, ensures fair trade, and supports U.S. businesses in the global marketplace.
  • D. Tuscany
    Tuscany is a central Italian region renowned for its rolling landscapes, historic cities like Florence and Siena, and its pivotal role in art, culture, and the birth of the Renaissance.
  • E. Senigallia
    Senigallia is a historic coastal town in Italy’s Marche region, known for its Adriatic seaside resort, Renaissance heritage, and well-preserved old town.
  • 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_69a498fc69ec8190b61722bd4b67c4d2 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c9df014081908a6e2f41ba012ecc completed March 1, 2026, 11:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0156109081908f163af94e4e7978 completed March 8, 2026, 4:55 a.m.
Created at: March 1, 2026, 8 p.m.