Triple
T5058245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mornington Peninsula |
E113957
|
entity |
| Predicate | approxDrivingTimeFromMelbourne |
P61012
|
FINISHED |
| Object | about 1 to 1.5 hours |
—
|
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: about 1 to 1.5 hours | Statement: [Mornington Peninsula, approxDrivingTimeFromMelbourne, about 1 to 1.5 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approxDrivingTimeFromMelbourne Context triple: [Mornington Peninsula, approxDrivingTimeFromMelbourne, about 1 to 1.5 hours]
-
A.
drivingTimeFromSydney
Indicates the amount of time it takes to drive from Sydney to a specified location.
-
B.
distanceToMelbourne
Indicates the spatial distance between a given location or entity and the city of Melbourne.
-
C.
distanceFromSydney
Indicates the spatial distance between a given location and the city of Sydney.
-
D.
distanceFromGeelong
Indicates the spatial distance between a given entity or location and Geelong.
-
E.
approximateDrivingTimeFromLAnse
Indicates the estimated amount of time it takes to drive from L'Anse to another specified location.
- 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_69bd443aa1f88190abb992d138f2cf42 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74523434819092b8b15992073b5b |
completed | March 20, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69bd715622b48190a3e8e49a5ef62b4a |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd738ac2e0819099c06cdcc5e21d28 |
completed | March 20, 2026, 4:19 p.m. |
Created at: March 20, 2026, 1:38 p.m.