Triple
T26386993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryder rental truck |
E663307
|
entity |
| Predicate | rentalCompany |
P160481
|
FINISHED |
| Object | Ryder |
—
|
NE NERFINISHED |
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: Ryder | Statement: [Ryder rental truck, rentalCompany, Ryder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rentalCompany Context triple: [Ryder rental truck, rentalCompany, Ryder]
-
A.
rentalModel
Indicates that one entity is used or provided to another under a specific rental arrangement, defining how the rental relationship is structured or operates.
-
B.
managementCompany
Indicates that one entity serves as the managing company responsible for overseeing or administering another entity.
-
C.
hasRentalShop
Indicates that one entity operates, owns, or is associated with a rental shop used to provide items or services for rent to others.
-
D.
offersEquipmentRental
Indicates that one entity provides equipment to another entity for temporary use in exchange for a fee or under a rental agreement.
-
E.
hasRentalCarCenter
Indicates that a location or facility includes or is associated with a rental car center where vehicles can be rented.
- 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_69ee88374adc81909868f3bab374a32f |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f610bc2b288190ae10e6c27e5df786 |
completed | May 2, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f5f800fa9c8190aab0962669fde8ac |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f6018ceb1c8190a6a5f84071659a96 |
completed | May 2, 2026, 1:52 p.m. |
Created at: April 26, 2026, 11:23 p.m.