Triple
T36398073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dundalk railway station |
E896541
|
entity |
| Predicate | isBorderStop |
P102304
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Dundalk railway station, isBorderStop, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBorderStop Context triple: [Dundalk railway station, isBorderStop, yes]
-
A.
hasBorderTerminus
Indicates that one entity serves as the endpoint or terminal location of another entity’s border or boundary.
-
B.
isBoundaryFor
Indicates that one entity serves as the limiting edge, border, or enclosing extent that defines the spatial or conceptual bounds of another entity.
-
C.
hasBoundaryStations
chosen
Indicates that an entity is associated with specific stations that mark its boundary or endpoints.
-
D.
hasBorderCheckpointOnOtherSide
Indicates that a border checkpoint is located on the opposite side of a boundary relative to a referenced point or entity.
-
E.
hasBorderCode
Indicates that there is an associated code or identifier specifying the type or status of a border between entities.
- 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_69f76e53b81081908d3b81860593f38a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.