Triple
T241761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airbnb |
E4944
|
entity |
| Predicate | businessModelIncludes |
P6233
|
FINISHED |
| Object | Peer-to-peer lodging |
—
|
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: Peer-to-peer lodging | Statement: [Airbnb, businessModelIncludes, Peer-to-peer lodging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: businessModelIncludes Context triple: [Airbnb, businessModelIncludes, Peer-to-peer lodging]
-
A.
usesBusinessModel
chosen
Indicates that one entity operates according to, or applies in practice, the business model defined or provided by another entity.
-
B.
formerBusinessModel
Indicates that an entity previously operated under a particular business model, but no longer does so.
-
C.
businessVenture
Indicates a relationship where entities jointly engage in, operate, or are involved with a commercial or entrepreneurial undertaking.
-
D.
includes
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
E.
economyIncludes
Indicates that an economy encompasses, contains, or is composed of the specified component, sector, or element.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b60ad308190b12f119960a8bde7 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.