Triple
T25685206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tlawng valley |
E644048
|
entity |
| Predicate | hasRiverCourseType |
P27890
|
FINISHED |
| Object | meandering course |
—
|
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: meandering course | Statement: [Tlawng valley, hasRiverCourseType, meandering course]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverCourseType Context triple: [Tlawng valley, hasRiverCourseType, meandering course]
-
A.
hasWatercourseType
chosen
Indicates the specific kind or category of watercourse (such as river, stream, or canal) associated with an entity.
-
B.
hasRiverBedType
Indicates the type or classification of the riverbed associated with a given river or watercourse.
-
C.
hasRiverineCharacteristic
Indicates that something possesses qualities, features, or conditions associated with rivers or river environments.
-
D.
isWatercourseOf
Indicates that a watercourse (such as a river or stream) flows through, belongs to, or is geographically associated with a particular area or feature.
-
E.
hasRiverCode
Indicates that a river is associated with a specific identifying code or classification value.
- 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_69e77e8046888190b07ffa58c7e2c37a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 21, 2026, 8:07 p.m.