Triple

T8230253
Position Surface form Disambiguated ID Type / Status
Subject Thyestes E192273 entity
Predicate associatedWith P37 FINISHED
Object Pisa in Elis E353312 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: Pisa in Elis | Statement: [Thyestes, associatedWith, Pisa in Elis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pisa in Elis
Context triple: [Thyestes, associatedWith, Pisa in Elis]
  • A. Elis (city) chosen
    Elis (city) was an ancient Greek city-state in the Peloponnese, known for overseeing the sanctuary of Olympia and the Olympic Games.
  • B. Pisa
    Pisa is a historic Italian city in Tuscany best known for its iconic Leaning Tower and as a significant center of medieval trade, learning, and architecture.
  • C. Pisae
    Pisae is the ancient Roman name for the city of Pisa in Tuscany, Italy, historically significant as a coastal settlement and later a prominent maritime republic.
  • D. Cortona
    Cortona is an ancient hilltop town in Tuscany, Italy, historically significant as one of the principal cities of the Etruscan civilization.
  • E. Marina di Pisa
    Marina di Pisa is a coastal town in Tuscany, Italy, known as a seaside resort near Pisa on the Ligurian Sea.
  • 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_69ca82db5b90819085d1ad7c2e27bfcc completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb78035b488190bfd6b6c5d7b7c002 completed March 31, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd34de56688190a7c33bbcb12cd7c1 completed April 1, 2026, 3:08 p.m.
Created at: March 30, 2026, 5:46 p.m.