Triple
T18296013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SL |
E438231
|
entity |
| Predicate | offersFeatures |
P9404
|
FINISHED |
| Object | additional comfort features |
—
|
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: additional comfort features | Statement: [SL, offersFeatures, additional comfort features]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersFeatures Context triple: [SL, offersFeatures, additional comfort features]
-
A.
offersFeature
chosen
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
B.
offersServiceIn
Indicates that a provider makes a particular service available within a specified location or jurisdiction.
-
C.
offersProduct
Indicates that one entity makes a product available to another entity, typically for sale or use.
-
D.
offersObject
Indicates that a subject provides or makes available a specific object to another party as an offer.
-
E.
offersTechnology
Indicates that one entity provides or makes available a technology or technological solution to another 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5017c0f04819095cd9d59afc37caa |
completed | April 19, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.