Triple

T10631805
Position Surface form Disambiguated ID Type / Status
Subject Via Aemilia Scauri E250474 entity
Predicate startPoint P389 FINISHED
Object Luni E688008 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: Luni | Statement: [Via Aemilia Scauri, startPoint, Luni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luni
Context triple: [Via Aemilia Scauri, startPoint, Luni]
  • A. Luni chosen
    Luni is an archaeological site and small town in northwestern Italy, known for the remains of the ancient Roman city of Luna near the Ligurian coast.
  • B. Luns
    Luns is a Dutch surname most notably associated with Joseph Luns, a former Dutch foreign minister and long-serving Secretary General of NATO.
  • C. Tarëno
    Tarëno is an alternative name for the Tiriyó language, a Cariban language spoken by the Tiriyó people in parts of Brazil and Suriname.
  • D. Lunxhëri
    Lunxhëri is a historic subregion of southern Albania known for its traditional stone villages, Orthodox heritage, and scenic mountainous landscapes.
  • E. Tresana
    Tresana is a small municipality in the Tuscany region of central Italy, known for its rural landscape and historic hilltop settlements.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6df94dc1c8190b6347eaf35a5acc2 completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96bb4bbf08190994ea9123c0b2dab completed April 10, 2026, 9:29 p.m.
Created at: April 8, 2026, 9:01 p.m.