Triple
T1543556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LUV |
E32924
|
entity |
| Predicate | associatedWithBusinessModel |
P6233
|
FINISHED |
| Object | no-frills service |
—
|
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: no-frills service | Statement: [LUV, associatedWithBusinessModel, no-frills service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithBusinessModel Context triple: [LUV, associatedWithBusinessModel, no-frills service]
-
A.
usesBusinessModel
chosen
Indicates that one entity operates according to, or applies in practice, the business model defined or provided by another entity.
-
B.
associatedCompanyBusinessModel
Indicates that there is a relationship linking a company to the specific business model it follows or employs.
-
C.
hasUnderlyingCompanyBusinessModel
Indicates that one entity possesses or is based on a specific company business model that underlies its structure, operations, or value creation.
-
D.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
E.
associatedWithUnit
Indicates that one entity has a connection, linkage, or affiliation with a particular unit (such as a division, department, or organizational subunit).
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa95c1a2948190a2b98469afec1a7d |
completed | March 6, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69a907b2453c8190a41f6b88c8217d1e |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.