Triple
T8800089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scarlet Lady |
E209381
|
entity |
| Predicate | hasWiFiPolicy |
P32735
|
FINISHED |
| Object | basic Wi-Fi 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: basic Wi-Fi included in fare | Statement: [Scarlet Lady, hasWiFiPolicy, basic Wi-Fi included in fare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWiFiPolicy Context triple: [Scarlet Lady, hasWiFiPolicy, basic Wi-Fi included in fare]
-
A.
supportsWiFiStandard
Indicates that one entity is compatible with and able to operate using a specified Wi-Fi communication standard defined by another entity.
-
B.
wifiAvailable
chosen
Indicates that a location, device, or context has access to a functioning Wi-Fi network.
-
C.
hasPolicySupport
Indicates that one entity provides endorsement, backing, or approval for a specific policy associated with another entity.
-
D.
hasEnrollmentPolicy
Indicates that there is a specific rule or set of rules governing who may enroll in, access, or participate in something and under what conditions.
-
E.
hasLightingPolicy
Indicates that there is a defined policy or set of rules governing how lighting is used, managed, or controlled for the related entity.
- 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.