Triple
T38608628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Car service |
E934413
|
entity |
| Predicate | luggageSpace |
P116491
|
FINISHED |
| Object | more generous than standard class |
—
|
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: more generous than standard class | Statement: [Green Car service, luggageSpace, more generous than standard class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: luggageSpace Context triple: [Green Car service, luggageSpace, more generous than standard class]
-
A.
hasOnboardLuggageSpace
chosen
Indicates that an entity provides or includes dedicated space for carrying luggage on board.
-
B.
allowsLuggage
Indicates that one entity permits another entity to bring or carry luggage in a given context.
-
C.
hasLuggage
Indicates that an entity is carrying, possessing, or associated with one or more pieces of luggage.
-
D.
cargoSpace
Indicates that one entity provides storage capacity or room for carrying goods, equipment, or other items for another entity.
-
E.
hasBaggageSystem
Indicates that an entity is equipped with or utilizes a baggage handling 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_69f76eccd6d081909ccce171011739a1 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdb0de8c08190928cd1323f80ab5c |
completed | May 7, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69fcd9017dd88190b32a73fe78909740 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.