Triple
T13044893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rotten Sea |
E327291
|
entity |
| Predicate | describesFeatureType |
P5048
|
FINISHED |
| Object | system of shallow hypersaline lagoons |
—
|
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: system of shallow hypersaline lagoons | Statement: [Rotten Sea, describesFeatureType, system of shallow hypersaline lagoons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describesFeatureType Context triple: [Rotten Sea, describesFeatureType, system of shallow hypersaline lagoons]
-
A.
featureType
chosen
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
B.
datumType
Indicates the specific kind or category of data that characterizes or classifies a datum.
-
C.
includesFeatureTypes
Indicates that an entity contains or encompasses specific types of features as part of its composition or definition.
-
D.
definitionType
Indicates the specific kind or category of definition that characterizes how one entity is defined in relation to another.
-
E.
namedFeature
Indicates that an entity has a specific feature or attribute that is explicitly given a name.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98a9829b48190b23624b6b3df4600 |
completed | April 10, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69d9803aca4c8190b1015cd159cc47a9 |
completed | April 10, 2026, 10:56 p.m. |
Created at: April 9, 2026, 8:56 p.m.