Triple
T3740086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T1 HD truck platform |
E79676
|
entity |
| Predicate | supportsBedConfiguration |
P40663
|
FINISHED |
| Object | standard bed |
—
|
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: standard bed | Statement: [T1 HD truck platform, supportsBedConfiguration, standard bed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsBedConfiguration Context triple: [T1 HD truck platform, supportsBedConfiguration, standard bed]
-
A.
hasBedType
chosen
Indicates that an entity (such as a room or accommodation) is associated with a specific type or configuration of bed.
-
B.
beds
Indicates that one entity provides or designates a place for another entity to sleep or rest.
-
C.
bedLengthOption
Indicates the available or specified length configuration of a bed as an option.
-
D.
cabinConfiguration
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
-
E.
bedName
Indicates the specific name or designation assigned to a bed within a given context or system.
- 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_69ad8b115610819095b02007da5ca3cb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb5344fc8190b183aca5c04e3bcc |
completed | March 8, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69adc048f28c819092bed16a95a3cac1 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.