Triple
T15729269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Mashu |
E381297
|
entity |
| Predicate | hasNoLargeRiversFlowingIn |
P119961
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Lake Mashu, hasNoLargeRiversFlowingIn, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoLargeRiversFlowingIn Context triple: [Lake Mashu, hasNoLargeRiversFlowingIn, true]
-
A.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
B.
hasNumberOfRivers
Indicates the quantitative relationship specifying how many rivers are associated with a given entity.
-
C.
hasNoCoastline
Indicates that the referenced place is landlocked and does not border any sea or ocean.
-
D.
hasBodyOfWaterDrainedBy
Indicates that a body of water is emptied or its water flow is carried away by a specified draining feature, such as a river, channel, or drainage system.
-
E.
hasMajorRiverSystem
Indicates that an entity possesses or is traversed by a primary, large-scale river network that significantly characterizes its hydrology or geography.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fb4cc0081909efe330339474017 |
completed | April 16, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69e00526759c819088b80d85138b8974 |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e0094af5b481908ad51d5d7ba0c726 |
completed | April 15, 2026, 9:55 p.m. |
Created at: April 10, 2026, 4:46 a.m.