Triple
T31981914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Aeron |
E816603
|
entity |
| Predicate | hasApproximateLengthCategory |
P191364
|
FINISHED |
| Object | small river |
—
|
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: small river | Statement: [River Aeron, hasApproximateLengthCategory, small river]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateLengthCategory Context triple: [River Aeron, hasApproximateLengthCategory, small river]
-
A.
hasMaxLengthApprox
Indicates that something has a maximum length that is approximately equal to a specified value, allowing for some tolerance or imprecision.
-
B.
rangeLengthApprox
Indicates that the length or extent of a range is approximately equal to a specified value, allowing for some tolerance or imprecision.
-
C.
hasNameLengthCategory
Indicates that an entity is associated with a classification describing the length of its name (e.g., short, medium, long).
-
D.
hasApproximateNumberOfLetters
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
-
E.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
- 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_69f348f6a3008190bfb59ca695fd68e2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
| PDg | Predicate description generation | batch_69fcdf22ab8881908b257f16522920c5 |
completed | May 7, 2026, 6:51 p.m. |
Created at: May 1, 2026, 12:12 a.m.