Triple
T34949834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Australia–South Australia border |
E1007958
|
entity |
| Predicate | hasNamedCrossingPoint |
P50696
|
FINISHED |
| Object | Border Village |
—
|
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: Border Village | Statement: [Western Australia–South Australia border, hasNamedCrossingPoint, Border Village]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamedCrossingPoint Context triple: [Western Australia–South Australia border, hasNamedCrossingPoint, Border Village]
-
A.
hasCrossingPoint
chosen
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
-
B.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
C.
hasNearbyCrossingPoint
Indicates that one location has a crossing point (such as a bridge, crosswalk, or intersection) situated close to it.
-
D.
hasConfluencePointAt
Indicates that two or more flows, paths, or entities meet and merge at a specific point.
-
E.
hasCrossingLoops
Indicates that the related structure or path contains loops that intersect or cross over themselves.
- 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff2d22ffb48190ae58ddf3c7e02869 |
completed | May 9, 2026, 12:48 p.m. |
| PD | Predicate disambiguation | batch_69ff2ac2e1c4819096cc64e94aef2ff0 |
completed | May 9, 2026, 12:38 p.m. |
Created at: May 3, 2026, 4 p.m.