Triple
T31937902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soviet War Memorial (Treptower Park) |
E815440
|
entity |
| Predicate | totalHeightWithMound |
P8271
|
FINISHED |
| Object | about 30 meters |
—
|
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: about 30 meters | Statement: [Soviet War Memorial (Treptower Park), totalHeightWithMound, about 30 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalHeightWithMound Context triple: [Soviet War Memorial (Treptower Park), totalHeightWithMound, about 30 meters]
-
A.
maximumMoundHeight
Indicates the greatest allowable or observed height of a mound relative to a specified reference or context.
-
B.
centralMoundHeight
Indicates the height measurement of a central mound relative to a defined reference level.
-
C.
numberOfMounds
Indicates the quantitative relationship specifying how many mounds are associated with a given entity or context.
-
D.
totalHeight
chosen
Indicates the combined vertical measurement resulting from adding the heights of one or more entities.
-
E.
moundColor
Indicates the color associated with a mound.
- 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_69f348f3035c81908558e2339955abb3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f760a35b988190904e6267553ad2fe |
completed | May 3, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f75eb3d6f081908c933474eb359e3d |
completed | May 3, 2026, 2:41 p.m. |
Created at: May 1, 2026, 12:05 a.m.