Triple
T2641599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Junction Railway |
E62878
|
entity |
| Predicate | linkedNetwork |
P42454
|
FINISHED |
| Object | early British main line railway network |
—
|
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: early British main line railway network | Statement: [Grand Junction Railway, linkedNetwork, early British main line railway network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedNetwork Context triple: [Grand Junction Railway, linkedNetwork, early British main line railway network]
-
A.
linkType
Indicates the specific kind or category of relationship that connects two linked entities.
-
B.
branchNetwork
Indicates that one entity operates as a branch or local outlet within the wider organizational or operational network of another entity.
-
C.
linkedPosition
Indicates that one position is associated or connected to another position in a defined way.
-
D.
linkedCity
Indicates that two entities are associated with each other through a specific city, such as being located in, connected via, or related by that city.
-
E.
connectedLine
Indicates that two entities are joined by a continuous line or linear connection.
- 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd8fdc0bc8190b7fd102b87ee50d1 |
completed | March 7, 2026, 7:51 a.m. |
| PD | Predicate disambiguation | batch_69abd812849881908f956845a80e0205 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd8abcc348190bfa05c0abc4bcee7 |
completed | March 7, 2026, 7:50 a.m. |
Created at: March 6, 2026, 9:53 p.m.