Triple

T16448694
Position Surface form Disambiguated ID Type / Status
Subject Stato da Mar E399497 entity
Predicate hasPart P35 FINISHED
Object Scutari E572765 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: Scutari | Statement: [Stato da Mar, hasPart, Scutari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scutari
Context triple: [Stato da Mar, hasPart, Scutari]
  • A. Scutari chosen
    Scutari, also known as Üsküdar, is a historic district on the Asian side of Istanbul overlooking the Bosphorus.
  • B. Monastir
    Monastir is a coastal city in central-eastern Tunisia, known as a historic port and the birthplace and burial place of the country’s first president, Habib Bourguiba.
  • C. Monastir
    Monastir, known today as Bitola in North Macedonia, is a historic Balkan city that played a significant strategic role during World War I.
  • D. Monastir
    Monastir is a small town and municipality in southern Sardinia, Italy, known for its agricultural activities and proximity to the regional capital Cagliari.
  • E. Prizren
    Prizren is a historic and culturally rich city in southern Kosovo, known for its well-preserved Ottoman-era architecture and diverse religious heritage.
  • 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_6a00cfbbbb888190b750d8f4c005ee42 completed May 10, 2026, 6:34 p.m.
Created at: April 10, 2026, 5:10 a.m.