Triple
T17594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlantic Ocean |
E347
|
entity |
| Predicate | hasSalinityRange |
P1181
|
FINISHED |
| Object | about 33 to 37 parts per thousand |
—
|
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 33 to 37 parts per thousand | Statement: [Atlantic Ocean, hasSalinityRange, about 33 to 37 parts per thousand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSalinityRange Context triple: [Atlantic Ocean, hasSalinityRange, about 33 to 37 parts per thousand]
-
A.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
B.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
C.
hasLimitation
Indicates that an entity is subject to a constraint, restriction, or boundary that limits its scope, capability, or applicability.
-
D.
majorPortAtMouth
Indicates that a major port is located at the mouth of a river where it meets a larger body of water.
-
E.
hasCoastlineOn
Indicates that one entity’s coastline borders or is directly adjacent to a specified body of water.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a242494a548190a5776fb6cad4d4af |
completed | Feb. 28, 2026, 1:18 a.m. |
| PD | Predicate disambiguation | batch_69a23fedf0fc8190ad99bd1da297b14d |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a242489dbc819092c100d3fbf130ef |
completed | Feb. 28, 2026, 1:18 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.