Triple
T11095237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal First Class |
E262359
|
entity |
| Predicate | relativeRankInCabins |
P22893
|
FINISHED |
| Object | above business class |
—
|
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: above business class | Statement: [Royal First Class, relativeRankInCabins, above business class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeRankInCabins Context triple: [Royal First Class, relativeRankInCabins, above business class]
-
A.
rankComparedTo
chosen
Indicates the relative ordering or position of one entity in comparison to another based on a specified ranking criterion.
-
B.
comfortLevelComparedToPremiumCabins
Indicates how the comfort level of something compares relative to that of premium cabins.
-
C.
rankedAmong
Indicates that an entity holds a specific position or status within a defined group, list, or hierarchy of comparable entities.
-
D.
attendanceRank
Indicates the relative position or level of an entity in terms of how frequently or consistently it attends compared to others.
-
E.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a0897188190b6c293b44990b3d4 |
completed | April 9, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_69d7441aa3548190b92dbde57841c135 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.