Triple

T29548300
Position Surface form Disambiguated ID Type / Status
Subject Polis Massa medical facility E749688 entity
Predicate transportFacilities P25244 FINISHED
Object landing bays for starships 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: landing bays for starships | Statement: [Polis Massa medical facility, transportFacilities, landing bays for starships]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: transportFacilities
Context triple: [Polis Massa medical facility, transportFacilities, landing bays for starships]
  • A. transportationFacility chosen
    Indicates that one entity is a facility or location used for the transportation or transit of people or goods in relation to another entity.
  • B. transportationJunctionFor
    Indicates a location that serves as a connecting point where multiple transportation routes or modes meet, intersect, or transfer.
  • C. transportHubType
    Indicates the specific category or kind of transport hub associated with an entity (e.g., airport, train station, bus terminal).
  • D. transportDevelopment
    Indicates the development or improvement of transportation systems, infrastructure, or services connecting places or entities.
  • E. transportationHubType
    Indicates the specific kind of transportation hub an entity is (e.g., airport, train station, bus terminal).
  • 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_69f0bd48691081908cecad39bac591e0 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69fd6a1c1c4881908090053bc359b181 completed May 8, 2026, 4:44 a.m.
PD Predicate disambiguation batch_69fd696f24d8819091033afacbdaadc5 completed May 8, 2026, 4:41 a.m.
Created at: April 28, 2026, 5:09 p.m.