Triple
T37288046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trans-Australian Railway corridor |
E925586
|
entity |
| Predicate | hasCrossingLoops |
P193862
|
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: [Trans-Australian Railway corridor, hasCrossingLoops, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrossingLoops Context triple: [Trans-Australian Railway corridor, hasCrossingLoops, yes]
-
A.
hasVerticalLoops
Indicates that one entity features or includes vertical loop structures in its form, design, or configuration.
-
B.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
C.
hasCrossingPoint
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
-
D.
hasNumberOfCrosses
Indicates the quantity of crosses associated with or present on a given entity.
-
E.
hasAlternativeCrossing
Indicates that there exists another available crossing option that can be used instead of the primary one.
- 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_69f76eafe20c8190856d3b996a4c31a7 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd57ba740c8190bd1d40166fccccb7 |
completed | May 8, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69fd55ee82b881908a639da3a41b3af6 |
completed | May 8, 2026, 3:18 a.m. |
| PDg | Predicate description generation | batch_69fd57b9cdec81908536c4159e375931 |
completed | May 8, 2026, 3:25 a.m. |
Created at: May 3, 2026, 4:16 p.m.