Triple
T5824501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HawaiianMiles |
E129188
|
entity |
| Predicate | supportsMobileAppAccess |
P14571
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [HawaiianMiles, supportsMobileAppAccess, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsMobileAppAccess Context triple: [HawaiianMiles, supportsMobileAppAccess, yes]
-
A.
supportsDeviceManagement
Indicates that one entity provides capabilities or functionality to manage, configure, or control another entity’s devices.
-
B.
supportsThirdPartyApplications
Indicates that an entity is capable of working with, integrating, or allowing the use of software applications developed by external third parties.
-
C.
supportsConditionalAccess
Indicates that one entity enables or is compatible with applying conditional access controls or policies to another entity or interaction.
-
D.
allowsMobileReception
Indicates that one entity provides the conditions or infrastructure necessary for another entity to receive mobile (cellular) network service.
-
E.
hasApp
chosen
Indicates that an entity possesses, provides, or is associated with a particular application.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0333fdd7081908d829265caa2ac11 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:53 p.m.