Triple

T38059738
Position Surface form Disambiguated ID Type / Status
Subject Shanwick Oceanic FIR E950306 entity
Predicate coordinatesWith P1140 FINISHED
Object Santa Maria Oceanic FIR
Santa Maria Oceanic FIR is a major North Atlantic oceanic flight information region managed by Portugal’s air navigation service, responsible for controlling transatlantic air traffic in its sector.
E2255009 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: Santa Maria Oceanic FIR | Statement: [Shanwick Oceanic FIR, coordinatesWith, Santa Maria Oceanic FIR]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Santa Maria Oceanic FIR
Triple: [Shanwick Oceanic FIR, coordinatesWith, Santa Maria Oceanic FIR]
Generated description
Santa Maria Oceanic FIR is a major North Atlantic oceanic flight information region managed by Portugal’s air navigation service, responsible for controlling transatlantic air traffic in its sector.

Provenance (5 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_69f76f01e63c819093b6012fc974f35a completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbca07fa488190adae00afbd769d4d completed May 6, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a415d377d64819090ab72aad87f98f0 completed June 28, 2026, 5:43 p.m.
NEDg Description generation batch_6a415dba142c8190ac690666c2a2db65 completed June 28, 2026, 5:45 p.m.
NED2 Entity disambiguation (via description) batch_6a415f782d9881909ed47dd8690ce40f completed June 28, 2026, 5:52 p.m.
Created at: May 3, 2026, 4:21 p.m.