Triple
T11204180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miles&Go |
E265116
|
entity |
| Predicate | earningChannel |
P97841
|
FINISHED |
| Object | TAP Air Portugal flights |
—
|
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: TAP Air Portugal flights | Statement: [Miles&Go, earningChannel, TAP Air Portugal flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earningChannel Context triple: [Miles&Go, earningChannel, TAP Air Portugal flights]
-
A.
learn
Indicates that an entity acquires knowledge, skills, or understanding from another entity, source, or experience.
-
B.
educationalFocus
Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
-
C.
educationProxy
Indicates that one entity serves as a stand-in or representative for another entity in matters related to education or educational status.
-
D.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
E.
courseEndPoint
Indicates the final location or destination at which a course, route, or path terminates.
- F. None of above. chosen
Provenance (4 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d355c481908fc3d555b596314d |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf83464819087529d47d025d313 |
completed | April 9, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.