Triple
T24287169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greensborough, Victoria |
E605701
|
entity |
| Predicate | distanceFromMelbourneCBD_km |
P21893
|
FINISHED |
| Object | approximately 17 |
—
|
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: approximately 17 | Statement: [Greensborough, Victoria, distanceFromMelbourneCBD_km, approximately 17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMelbourneCBD_km Context triple: [Greensborough, Victoria, distanceFromMelbourneCBD_km, approximately 17]
-
A.
distanceToMelbourne
chosen
Indicates the spatial distance between a given location or entity and the city of Melbourne.
-
B.
distanceFromGeelong
Indicates the spatial distance between a given entity or location and Geelong.
-
C.
distanceFromSydney
Indicates the spatial distance between a given location and the city of Sydney.
-
D.
distanceToMildura_km
Indicates the physical distance, measured in kilometers, between a given location and Mildura.
-
E.
distanceFromFlindersStreet
Indicates the spatial distance between a given location and Flinders Street.
- 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f56cdc08190a1e06f67dffd4769 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:08 a.m.