Triple
T5297115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pioneer Monument |
E119881
|
entity |
| Predicate | pedestalHeightSymbolizes |
P63874
|
FINISHED |
| Object | depth of snow during the Donner Party winter of 1846–1847 |
—
|
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: depth of snow during the Donner Party winter of 1846–1847 | Statement: [Pioneer Monument, pedestalHeightSymbolizes, depth of snow during the Donner Party winter of 1846–1847]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pedestalHeightSymbolizes Context triple: [Pioneer Monument, pedestalHeightSymbolizes, depth of snow during the Donner Party winter of 1846–1847]
-
A.
statueHeight
Indicates the height measurement of a statue in some specified unit.
-
B.
heightWithPedestal
Indicates the total vertical measurement of an object including the height of its supporting pedestal.
-
C.
highestPillarApproximateHeight
Indicates the estimated height value of the tallest pillar in a given context or structure.
-
D.
elevationToCathedral
Indicates the formal act or process by which a church is raised in status to become a cathedral.
-
E.
symbolicMountain
Indicates that a mountain functions as a symbol or emblem representing some idea, value, or entity.
- F. None of above. chosen
Provenance (4 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_69bd446f22b88190b6a47fb91c68a3e7 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8e44e7c881909b241b2fec366038 |
completed | March 20, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69bd845097ac81909678624c4907fda4 |
completed | March 20, 2026, 5:30 p.m. |
| PDg | Predicate description generation | batch_69bd8e43c4c88190bb72b9bf56c99425 |
completed | March 20, 2026, 6:13 p.m. |
Created at: March 20, 2026, 1:53 p.m.