Triple
T913503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flight to Varennes |
E19716
|
entity |
| Predicate | transportUsed |
P11822
|
FINISHED |
| Object | large berline carriage |
—
|
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: large berline carriage | Statement: [Flight to Varennes, transportUsed, large berline carriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportUsed Context triple: [Flight to Varennes, transportUsed, large berline carriage]
-
A.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
B.
transportationFunction
Indicates that one entity serves to move or carry another entity from one place to another.
-
C.
transportFor
chosen
Indicates a relationship where one entity serves as the means or service used to move another entity from one place to another.
-
D.
transports
Indicates that one entity carries or conveys another entity from one place to another.
-
E.
transportRole
Indicates that an entity participates in a transportation process with a specific functional role (e.g., carrier, passenger, cargo, or operator).
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b6755c488190b7f7848110e3ea2c |
completed | March 1, 2026, 9:58 p.m. |
| PD | Predicate disambiguation | batch_69a4b292d3408190947cbc2f794cf8c5 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:39 p.m.