Triple
T21836942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M923 |
E539143
|
entity |
| Predicate | canCarryPassengersInCargoArea |
P145506
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [M923, canCarryPassengersInCargoArea, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canCarryPassengersInCargoArea Context triple: [M923, canCarryPassengersInCargoArea, true]
-
A.
hasPassengerArea
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
-
B.
hasCargoAccess
Indicates that an entity has the ability or permission to access a designated cargo area or its contents.
-
C.
cargoCapacityFeature
Indicates that an entity has a feature specifying how much cargo it can carry or accommodate.
-
D.
designedCargoCapacity
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
-
E.
cargoSpace
Indicates that one entity provides storage capacity or room for carrying goods, equipment, or other items for another entity.
- 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_69e0c475cda88190987d08f23caebdc1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0a7a890208190a902184e60194e1c |
completed | April 28, 2026, 12:27 p.m. |
| PD | Predicate disambiguation | batch_69e6be8c14748190bdcc44a14d50bea4 |
completed | April 21, 2026, 12:02 a.m. |
| PDg | Predicate description generation | batch_69e6c187bc548190b4ca13150f6bae38 |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 6:55 p.m.