Triple
T27695326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunlop Bridge |
E698274
|
entity |
| Predicate | hasSectionOfTrackUnder |
P79289
|
FINISHED |
| Object | start of the Dunlop Curve |
—
|
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: start of the Dunlop Curve | Statement: [Dunlop Bridge, hasSectionOfTrackUnder, start of the Dunlop Curve]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionOfTrackUnder Context triple: [Dunlop Bridge, hasSectionOfTrackUnder, start of the Dunlop Curve]
-
A.
hasTrackSection
Indicates that an entity includes, is composed of, or is associated with a specific section or segment of a track.
-
B.
partOfTrack
chosen
Indicates that something is a segment or component belonging to a larger track or route.
-
C.
hasSingleTrackSections
Indicates that a route or railway line includes sections where only a single track is available for traffic.
-
D.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
-
E.
hasSectionAlong
Indicates that one entity includes or runs along a specific segment or portion of another entity.
- 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_69ef590ea74081908f0cd7500d85fa27 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
Created at: April 27, 2026, 2:54 p.m.