Triple
T6791636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wulingyuan Scenic and Historic Interest Area |
E155944
|
entity |
| Predicate | numberOfSandstonePillarsAndPeaks |
P48325
|
FINISHED |
| Object | over 3000 |
—
|
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: over 3000 | Statement: [Wulingyuan Scenic and Historic Interest Area, numberOfSandstonePillarsAndPeaks, over 3000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSandstonePillarsAndPeaks Context triple: [Wulingyuan Scenic and Historic Interest Area, numberOfSandstonePillarsAndPeaks, over 3000]
-
A.
numberOfMountains
Indicates the quantitative count of mountains associated with a given entity or context.
-
B.
numberOfPeaks
chosen
Indicates the count of distinct peak points or maximum values present within a given entity or dataset.
-
C.
numberOfStones
Indicates the quantitative count of stones associated with a given entity or context.
-
D.
isOneOfHighestPeaksIn
Indicates that an entity is among the tallest or most elevated peaks within a specified group, region, or category.
-
E.
hasApproximateNumberOfHills
Indicates that an entity is associated with an estimated or imprecise count of hills rather than an exact number.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ae4d1c819089ac6b3abf11a341 |
completed | March 27, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d0979ce0819094678896da4e3169 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:15 p.m.