Triple
T4289902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake McKenzie |
E97362
|
entity |
| Predicate | hasApproxLength |
P34006
|
FINISHED |
| Object | about 1.2 kilometres |
—
|
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 1.2 kilometres | Statement: [Lake McKenzie, hasApproxLength, about 1.2 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproxLength Context triple: [Lake McKenzie, hasApproxLength, about 1.2 kilometres]
-
A.
hasMaxLengthApprox
chosen
Indicates that something has a maximum length that is approximately equal to a specified value, allowing for some tolerance or imprecision.
-
B.
hasApproximateDuration
Indicates that one entity has a duration that is estimated or not exact, typically expressed as an approximate length of time.
-
C.
hasApproximateEnd
Indicates that an entity’s end point, time, or boundary is known only approximately rather than precisely.
-
D.
hasDimensionsApprox
Indicates that an entity has physical dimensions that are known only approximately, rather than as exact measurements.
-
E.
hasApproximateShape
Indicates that one entity has a shape that is similar to, but not exactly the same as, the shape of another 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35061f5448190b3356b29a9129160 |
completed | March 12, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69b347fc4c0c8190a7fcd814e27308a5 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.