Triple
T25104247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinchega National Park |
E628822
|
entity |
| Predicate | formerPropertyName |
P65
|
FINISHED |
| Object | Kinchega Station |
—
|
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: Kinchega Station | Statement: [Kinchega National Park, formerPropertyName, Kinchega Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerPropertyName Context triple: [Kinchega National Park, formerPropertyName, Kinchega Station]
-
A.
formerName
chosen
Indicates that an entity was previously known by a different name in the past.
-
B.
formerComponentName
Indicates that an entity previously had a different component name before being renamed or replaced.
-
C.
formerMemberName
Indicates that the referenced name belongs to an entity that was previously a member of a particular group, organization, or body but is no longer one.
-
D.
formerLabel
Indicates that an entity previously had a certain label or designation, but no longer holds it.
-
E.
formerField
Indicates that an entity previously had a particular field, role, or area of activity, but no longer does.
- 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_69e2ff3071548190b62d1ac237397197 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 18, 2026, 6:26 a.m.