Triple

T16448684
Position Surface form Disambiguated ID Type / Status
Subject Stato da Mar E399497 entity
Predicate hasPart P35 FINISHED
Object Morea E37090 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: Morea | Statement: [Stato da Mar, hasPart, Morea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Morea
Context triple: [Stato da Mar, hasPart, Morea]
  • A. Morea chosen
    Morea was the medieval name for the Peloponnese peninsula in southern Greece, which served as a significant Byzantine province and later despotate.
  • B. Capurso
    Capurso is a small town and comune in the Apulia region of southern Italy, situated near the city of Bari.
  • C. Fabrezan
    Fabrezan is a small commune in the Aude department of southern France, known for its wine production and picturesque location in the Corbières region.
  • D. Provadia
    Provadia is a historic town in northeastern Bulgaria known for its ancient salt production and nearby prehistoric settlement, considered one of Europe's earliest urban centers.
  • E. Populonia
    Populonia was an important ancient coastal city of Etruria, known for its maritime trade, metalworking, and strategic position on the Tyrrhenian 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32cdee44c8190ae0df20c58ff7558 completed April 18, 2026, 7:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f4b738881908f8a205466397f33 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:10 a.m.