Triple

T9814049
Position Surface form Disambiguated ID Type / Status
Subject Alessandria E238351 entity
Predicate twinTown P1072 FINISHED
Object Vila Real E224908 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: Vila Real | Statement: [Alessandria, twinTown, Vila Real]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vila Real
Context triple: [Alessandria, twinTown, Vila Real]
  • A. Vila Real chosen
    Vila Real is a historic city in northern Portugal known for its scenic Douro Valley surroundings and notable Baroque architecture.
  • B. Santo Tirso
    Santo Tirso is a municipality in northern Portugal known for its textile industry, historic monasteries, and location in the Porto metropolitan area.
  • C. Sabugal
    Sabugal is a historic municipality and town in central Portugal, known for its medieval castle and scenic location near the Spanish border.
  • D. Sabrosa
    Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
  • E. Vila Real de Santo António
    Vila Real de Santo António is a coastal town and municipality in Portugal’s Algarve region, located at the mouth of the Guadiana River on the border with Spain.
  • 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_69ca84defac48190abc1148804f184c1 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb2f19660819083e3f15780352052 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc67db68819093217c9a74e72fbf completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:30 p.m.