Triple

T13017287
Position Surface form Disambiguated ID Type / Status
Subject Malian Gulf E322585 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Antikyra E132837 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: Antikyra | Statement: [Malian Gulf, hasNearbySettlement, Antikyra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antikyra
Context triple: [Malian Gulf, hasNearbySettlement, Antikyra]
  • A. Anticyra chosen
    Anticyra is an ancient Greek coastal town in the region of Phocis, historically noted for its harbor and its association with medicinal hellebore.
  • B. Siklós
    Siklós is a historic town in southern Hungary known for its medieval castle and wine-producing region.
  • C. Sigeion
    Sigeion was an ancient Greek city in the Troad region near the entrance to the Hellespont, strategically important for controlling access to the Black Sea.
  • D. Antistia
    Antistia was the first wife of the Roman general and statesman Pompey the Great, whom he married early in his political career.
  • E. Ankyra
    Ankyra is the ancient name of the city that later became Ankara, the capital of modern Turkey.
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97ece22908190a0941e23df7c774d completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c1147974819090007c21383d5c86 completed May 3, 2026, 3:29 a.m.
Created at: April 9, 2026, 8:51 p.m.