Triple
T254210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southwest Airlines |
E5400
|
entity |
| Predicate | offersInFlightWiFi |
P8861
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Southwest Airlines, offersInFlightWiFi, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersInFlightWiFi Context triple: [Southwest Airlines, offersInFlightWiFi, true]
-
A.
airSupport
Indicates that one entity provides aerial assistance or backing to another, typically through aircraft-based protection, transport, or attack.
-
B.
offersProgramsIn
Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
-
C.
numberOfFlights
Indicates the total count of flights associated with a given entity or within a specified context.
-
D.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
E.
airlineHub
Indicates that a particular location (typically an airport or city) serves as a central hub or primary operational base for an airline.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d548cac819081b1636b2a057c62 |
completed | Feb. 28, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69a25b678d6c81909780e1995c1ca691 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c2ca46c81908c61696f31e59a98 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.