Triple

T15286381
Position Surface form Disambiguated ID Type / Status
Subject Ob Bay E365410 entity
Predicate hasMajorPortNearby P5648 FINISHED
Object Sabetta E372434 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: Sabetta | Statement: [Ob Bay, hasMajorPortNearby, Sabetta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sabetta
Context triple: [Ob Bay, hasMajorPortNearby, Sabetta]
  • A. Sabetta chosen
    Sabetta is a remote port settlement on the Yamal Peninsula in Arctic Russia, known primarily as a key hub for liquefied natural gas (LNG) exports from the Yamal LNG project.
  • B. Nalut
    Nalut is a town in western Libya situated in the Nafusa Mountains, known for its Amazigh (Berber) heritage and historic hilltop granaries.
  • C. Nicotera
    Nicotera is a historic coastal town in the Calabria region of southern Italy, known for its medieval center and views over the Tyrrhenian Sea.
  • D. Gela Sule
    Gela Sule is a variant name for Nggela Sule, a locality associated with the Nggela (Florida) Islands in the Solomon Islands.
  • E. Tebet
    Tebet is a densely populated urban district in South Jakarta, Indonesia, known for its residential neighborhoods, commercial areas, and busy traffic corridors.
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00e551bb0819094db097285443740 completed April 15, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69feef798a588190981c77e6f4c6be78 completed May 9, 2026, 8:25 a.m.
Created at: April 10, 2026, 3:15 a.m.