Triple
T396298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victoria Falls |
E8989
|
entity |
| Predicate | hasPeakFlowMonths |
P6433
|
FINISHED |
| Object | February to May |
—
|
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: February to May | Statement: [Victoria Falls, hasPeakFlowMonths, February to May]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPeakFlowMonths Context triple: [Victoria Falls, hasPeakFlowMonths, February to May]
-
A.
hasSeasonalPattern
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
-
B.
hasMonth
chosen
Indicates that something is associated with, occurs in, or is assigned to a specific month.
-
C.
hasPeak
Indicates that something possesses or contains a highest point, summit, or maximum value.
-
D.
hasVariableMonth
Indicates that something is associated with or occurs in a month that can change rather than being fixed.
-
E.
hasAverageMonthLength
Indicates that an entity is associated with a specified average length of a month, typically expressed in days.
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec8a941081909a152fda0ce24a98 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96bd3848190a66ca14dfbd26da5 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.