Triple

T15703989
Position Surface form Disambiguated ID Type / Status
Subject Ten Degree Channel E380660 entity
Predicate shippingHazard P1950 FINISHED
Object subject to strong currents during monsoon LITERAL 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: subject to strong currents during monsoon | Statement: [Ten Degree Channel, shippingHazard, subject to strong currents during monsoon]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: shippingHazard
Context triple: [Ten Degree Channel, shippingHazard, subject to strong currents during monsoon]
  • A. hasHazardousMaterialsRestrictions
    Indicates that there are rules or limitations governing the presence, handling, or transport of hazardous materials in relation to the subject.
  • B. shippingRisk
    Indicates the level or likelihood of potential loss, damage, or delay associated with transporting goods from one location to another.
  • C. hazmatSupport
    Indicates that one entity provides hazardous materials (hazmat) response or support services to another entity or situation.
  • D. hasNotableHazard
    Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
  • E. hazardType chosen
    Indicates the specific kind or category of hazard associated with an entity or situation.
  • F. None of above.

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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b4d6b5788190883746ee82c799f5 completed April 16, 2026, 10:07 a.m.
PD Predicate disambiguation batch_69e0051d639481909a10614e8f83e659 completed April 15, 2026, 9:37 p.m.
Created at: April 10, 2026, 4:45 a.m.