Triple
T9012611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brilliant Lady |
E215511
|
entity |
| Predicate | passengerPolicy |
P85720
|
FINISHED |
| Object | adults only |
—
|
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: adults only | Statement: [Brilliant Lady, passengerPolicy, adults only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerPolicy Context triple: [Brilliant Lady, passengerPolicy, adults only]
-
A.
baggagePolicyType
Indicates the specific category or type of baggage policy that applies in a given travel or transportation context.
-
B.
bookingPolicy
Indicates the rules or conditions that govern how bookings or reservations can be made, modified, or canceled between parties.
-
C.
farePolicyRelatedTo
Indicates a relationship where a fare policy is associated with, applies to, or governs a particular entity, context, or service.
-
D.
farePolicySupport
Indicates that there is a policy in place governing fares (such as prices, discounts, or rules) that is recognized, enabled, or supported in the given context.
-
E.
farePolicyType
Indicates the type or category of fare policy that governs how prices, rules, or conditions are applied.
- 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69f846f88190af65dfcf8bdd936a |
completed | April 1, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69cc5edf84408190aa5f57cb8bfd00e1 |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5f6dec4081909379bd57c02a5710 |
completed | March 31, 2026, 11:57 p.m. |
Created at: March 30, 2026, 7:06 p.m.