Triple
T6798193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finley railway precinct |
E156108
|
entity |
| Predicate | transportTheme |
P73049
|
FINISHED |
| Object | country branch line railways in New South Wales |
—
|
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: country branch line railways in New South Wales | Statement: [Finley railway precinct, transportTheme, country branch line railways in New South Wales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportTheme Context triple: [Finley railway precinct, transportTheme, country branch line railways in New South Wales]
-
A.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
B.
transports
Indicates that one entity carries or conveys another entity from one place to another.
-
C.
transportHubType
Indicates the specific category or kind of transport hub associated with an entity (e.g., airport, train station, bus terminal).
-
D.
transportationFunction
Indicates that one entity serves to move or carry another entity from one place to another.
-
E.
transportModeFamily
Indicates the general category or family of transportation mode to which a specific transport mode belongs (e.g., road, rail, air, water).
- 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_69c6881844448190a65822d9b39d7f88 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ca0c288190a990180fb7cfd08f |
completed | March 27, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69c6d099bf08819089a9f9894d037e74 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d2a8f9188190abbb8c730e7b5edf |
completed | March 27, 2026, 6:55 p.m. |
Created at: March 27, 2026, 2:15 p.m.