Triple
T31883187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aberystwyth Cliff Railway |
E813934
|
entity |
| Predicate | hasLowerStationAddress |
P195649
|
FINISHED |
| Object | Cliff Terrace, Aberystwyth |
—
|
NE NERFINISHED |
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: Cliff Terrace, Aberystwyth | Statement: [Aberystwyth Cliff Railway, hasLowerStationAddress, Cliff Terrace, Aberystwyth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLowerStationAddress Context triple: [Aberystwyth Cliff Railway, hasLowerStationAddress, Cliff Terrace, Aberystwyth]
-
A.
hasLowerStation
Indicates that one entity occupies a lower rank, status, or position in a hierarchy relative to another entity.
-
B.
hasLowerStationAt
Indicates that one entity has a subordinate or lower-ranked position relative to another entity within a hierarchical structure.
-
C.
hasLower
Indicates that one entity is positioned at a lower level, rank, or value relative to another entity.
-
D.
isLowUsageStation
Indicates that a station has relatively low levels of usage or activity compared to other stations.
-
E.
hasLowerPart
Indicates that one entity includes another entity as a component specifically located in its lower part or region.
- 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_69f348ed74bc81909846aaa6a3c7318c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
| PDg | Predicate description generation | batch_69fddd364c1481908794c9d423bdc2d7 |
completed | May 8, 2026, 12:55 p.m. |
Created at: April 30, 2026, 11:56 p.m.