Triple
T15382313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Königstein Fortress |
E367833
|
entity |
| Predicate | hasWellDepth |
P43725
|
FINISHED |
| Object | over 150 metres |
—
|
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 150 metres | Statement: [Königstein Fortress, hasWellDepth, over 150 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWellDepth Context triple: [Königstein Fortress, hasWellDepth, over 150 metres]
-
A.
hasAverageDepth
Indicates that an entity possesses a specified mean depth value, typically measured over its entire extent or area.
-
B.
hasUndergroundDepth
chosen
Indicates that one entity has a specified vertical extent or depth located below the ground surface relative to another reference or context.
-
C.
hasDepth
Indicates that an entity possesses a measurable extent or distance from its surface inward or from top to bottom.
-
D.
hasChannelDepth
Indicates that one entity specifies or records the depth measurement of a channel associated with another entity.
-
E.
hasWaterDepthCategory
Indicates the classification of something based on the range or category of its water depth.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e61928c81908852c355d537ed9c |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:19 a.m.