Triple
T8728398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rae Lakes Loop |
E207187
|
entity |
| Predicate | typicalLengthInKilometers |
P69216
|
FINISHED |
| Object | approximately 66 |
—
|
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 66 | Statement: [Rae Lakes Loop, typicalLengthInKilometers, approximately 66]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLengthInKilometers Context triple: [Rae Lakes Loop, typicalLengthInKilometers, approximately 66]
-
A.
lengthInKm
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
-
B.
trackLengthApproxKm
chosen
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
C.
mainStraightLengthKm
Indicates the length, measured in kilometers, of the primary straight segment associated with the entity.
-
D.
navigableLengthApproxKm
Indicates the approximate distance, measured in kilometers, over which something (typically a waterway) can be navigated.
-
E.
hasMainStraightLengthKm
Indicates the length in kilometers of the primary or main straight segment associated with an entity.
- 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d1890e0819088b271db51faa738 |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:37 p.m.