Triple
T8800090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scarlet Lady |
E209381
|
entity |
| Predicate | hasGratuityPolicy |
P15903
|
FINISHED |
| Object | gratuities included in fare |
—
|
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: gratuities included in fare | Statement: [Scarlet Lady, hasGratuityPolicy, gratuities included in fare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGratuityPolicy Context triple: [Scarlet Lady, hasGratuityPolicy, gratuities included in fare]
-
A.
hasDiningPolicy
Indicates that an entity enforces or follows a specific set of rules or guidelines related to dining or meal-related activities.
-
B.
hasReservationPolicy
Indicates that an entity specifies or is governed by a particular policy regarding how reservations are made, managed, or honored.
-
C.
farePolicySupport
chosen
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.
-
D.
farePolicyType
Indicates the type or category of fare policy that governs how prices, rules, or conditions are applied.
-
E.
hasHospitalityComponent
Indicates that something includes, involves, or is associated with a hospitality-related element, service, or function.
- 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_69ca836320e48190b5cf585b90a322c4 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fb8aab88190befed16301e08efc |
completed | March 31, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1f28ec8190a34311cb412920c2 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:44 p.m.