Triple

T7876501
Position Surface form Disambiguated ID Type / Status
Subject Municipality of The Hague E182867 entity
Predicate hasTwinTown P919 FINISHED
Object Antalya E14330 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: Antalya | Statement: [Municipality of The Hague, hasTwinTown, Antalya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antalya
Context triple: [Municipality of The Hague, hasTwinTown, Antalya]
  • A. Antalya chosen
    Antalya is a major resort city on Turkey’s Mediterranean coast, known for its beaches, historic old town, and role as a gateway to the Turkish Riviera.
  • B. Alanya
    Alanya is a popular Mediterranean resort city in southern Turkey, known for its beaches, historic castle, and role as a major tourism hub.
  • C. Marmaris
    Marmaris is a popular Turkish coastal resort city known for its beaches, marinas, and vibrant nightlife along the Mediterranean.
  • D. Bodrum
    Bodrum is a popular coastal city and resort town in southwestern Turkey, known for its beaches, nightlife, and historic landmarks such as Bodrum Castle.
  • E. Izmir
    Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean 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_69ca828a17248190b46defe758bc5ad3 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb39aa7ca88190b88a18f6a8971e51 completed March 31, 2026, 3:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc93556f0c8190b072c3ec4c8e93bd completed April 1, 2026, 3:39 a.m.
Created at: March 30, 2026, 4:57 p.m.