Triple
T35247155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winsford railway station |
E1017698
|
entity |
| Predicate | hasThroughLines |
P152594
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Winsford railway station, hasThroughLines, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThroughLines Context triple: [Winsford railway station, hasThroughLines, 2]
-
A.
hasLines
chosen
Indicates that one entity contains, is composed of, or is associated with one or more linear elements or line segments.
-
B.
hasInteroperableLines
Indicates that two or more systems, networks, or components can operate together seamlessly, exchanging and using each other’s outputs without special adaptation.
-
C.
hasStraightLines
Indicates that the related entity possesses or is characterized by straight, non-curved lines.
-
D.
hasDeepLevelLines
Indicates that one entity possesses or exhibits lines that extend to or occur at a deep level within a given structure or context.
-
E.
hasLinesThroughEachPoint
Indicates that for every point in the relevant space or set, there exists at least one line that passes through that point.
- 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_69f76de235048190b990070c23c51b6b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7b2f3a104819098ddd8909eaf596c |
completed | May 3, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f7b1b8a9fc8190a1279e67a2d12707 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:02 p.m.