Triple
T35206598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lower Mesa Falls |
E1016552
|
entity |
| Predicate | hasImpressiveDrop |
P118026
|
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: [Lower Mesa Falls, hasImpressiveDrop, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImpressiveDrop Context triple: [Lower Mesa Falls, hasImpressiveDrop, true]
-
A.
hasBuildUpsAndDrops
Indicates that something (such as a sequence, process, or composition) contains periods of gradual intensity increase (build-ups) followed by sudden or marked decreases or releases (drops).
-
B.
hasFinalDrop
Indicates that an entity experiences or possesses a last or concluding decrease, reduction, or decline in some quantity, state, or value.
-
C.
hasSheerDrop
chosen
Indicates that something features a steep, nearly vertical drop-off or cliff-like descent.
-
D.
hasNumberOfDrops
Indicates the quantity or count of drops associated with an entity or event.
-
E.
hasMelodicDrop
Indicates that a musical piece or section features a pronounced melodic drop, where the melody shifts dramatically in pitch, intensity, or texture to create a climactic or contrasting moment.
- 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_69f76ddf549c8190869d0af076fd2c28 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:02 p.m.