Triple
T244613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nevada Fall |
E5008
|
entity |
| Predicate | hasDropStyle |
P1609
|
FINISHED |
| Object | single main drop |
—
|
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: single main drop | Statement: [Nevada Fall, hasDropStyle, single main drop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDropStyle Context triple: [Nevada Fall, hasDropStyle, single main drop]
-
A.
hasStyle
chosen
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
B.
hasSubstyle
Indicates that one style is a more specific or subordinate variant of another style within a hierarchical style structure.
-
C.
hasHigherStyleThan
Indicates that one entity’s style is considered superior or more fashionable than another’s.
-
D.
hasNumberOfDrops
Indicates the quantity or count of drops associated with an entity or event.
-
E.
hasDisplayType
Indicates the type or category of display associated with an entity, such as the format, mode, or presentation style used to show its content.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b62839c8190824064fe5da6a92a |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.