Triple
T3300587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Economy Class |
E69319
|
entity |
| Predicate | typicalPassengerDemographics |
P25372
|
FINISHED |
| Object | wide range of ages and income levels |
—
|
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: wide range of ages and income levels | Statement: [Economy Class, typicalPassengerDemographics, wide range of ages and income levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPassengerDemographics Context triple: [Economy Class, typicalPassengerDemographics, wide range of ages and income levels]
-
A.
typicalProfile
Indicates that an entity represents the standard or most representative profile or pattern for another entity.
-
B.
typicalAudience
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
C.
demographicsDescriptor
chosen
Indicates a descriptive attribute or classification that characterizes the demographic properties of an entity or group.
-
D.
demographicsCharacteristic
Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
-
E.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
- 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_69ad859e529c8190a404273f53cb487d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0a66fcc819093931fe7a6507723 |
completed | March 8, 2026, 5:23 p.m. |
| PD | Predicate disambiguation | batch_69ada42625308190be257f16a623a410 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:11 p.m.