Triple
T35724115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salt Lake of Qom |
E1032559
|
entity |
| Predicate | waterLevelVariation |
P134618
|
FINISHED |
| Object | seasonal |
—
|
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: seasonal | Statement: [Salt Lake of Qom, waterLevelVariation, seasonal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterLevelVariation Context triple: [Salt Lake of Qom, waterLevelVariation, seasonal]
-
A.
waterLevelTrend
Indicates the direction and rate at which a body of water’s level is changing over time (e.g., rising, falling, or stable).
-
B.
waterLevelDifference
Indicates the magnitude of difference between two water levels, such as between locations, times, or measurement points.
-
C.
waterLevelRise
Indicates that the level of water in a given area or container has increased over time.
-
D.
waterLevelAffectedBy
Indicates that the water level of one entity changes as a result of the influence or impact of another entity or factor.
-
E.
waterLevelTransition
chosen
Indicates a change in water level from one state or value to another over time.
- 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_69f76e102b5881909e5d63a30a5cecbe |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fde49a084081909d99b1e0258169d5 |
completed | May 8, 2026, 1:26 p.m. |
| PD | Predicate disambiguation | batch_69fde1d04bd881909a46ecbbf18dfe59 |
completed | May 8, 2026, 1:14 p.m. |
Created at: May 3, 2026, 4:05 p.m.