Triple
T1418924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Echuca |
E31979
|
entity |
| Predicate | transportModeHistorically |
P2417
|
FINISHED |
| Object | paddle steamer |
—
|
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: paddle steamer | Statement: [Echuca, transportModeHistorically, paddle steamer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportModeHistorically Context triple: [Echuca, transportModeHistorically, paddle steamer]
-
A.
transportationTypeHistoricallyImportant
Indicates that a mode of transportation has played a significant role or had notable impact in historical events, periods, or developments.
-
B.
passesUsedForTransportation
Indicates that the passes are utilized as a means or instrument for transporting people or goods.
-
C.
historicalMigrationType
Indicates the type or category of migration that occurred in a historical context between entities.
-
D.
historicallyIn
Indicates that one entity existed, occurred, or was situated within the historical context, period, or jurisdiction associated with another entity.
-
E.
historicallyUsedFor
chosen
Indicates that something served a particular function or purpose at some point in the past, even if it may no longer be used that way now.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c40631e881909ddf81a2eb84af1c |
completed | March 1, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69a4bf060b0081909ba00e6ac093a28b |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.