Triple
T3881210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rain, Steam and Speed – The Great Western Railway |
E92825
|
entity |
| Predicate | inMuseumCollectionSince |
P52115
|
FINISHED |
| Object | 19th century |
—
|
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: 19th century | Statement: [Rain, Steam and Speed – The Great Western Railway, inMuseumCollectionSince, 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inMuseumCollectionSince Context triple: [Rain, Steam and Speed – The Great Western Railway, inMuseumCollectionSince, 19th century]
-
A.
museumHolds
Indicates that a museum possesses, preserves, or has custody of a particular item or collection within its holdings.
-
B.
museumInventoryNumber
Indicates the unique catalog or inventory identifier assigned to an item within a museum’s collection.
-
C.
hasMuseumFunction
Indicates that an entity serves the role or performs the function of a museum.
-
D.
openedAsMuseumIn
Indicates that a place or building began operating as a museum in a specified year or at a specified time.
-
E.
museumAt
Indicates that an entity (such as an exhibit, artifact, or event) is located at or associated with a particular museum.
- 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef14f9bb4819098e64b527b546d74 |
completed | March 9, 2026, 4:11 p.m. |
Created at: March 9, 2026, 3:20 p.m.