Triple
T23842320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castra Regina |
E591020
|
entity |
| Predicate | hasSubsequentUse |
P5014
|
FINISHED |
| Object | basis for medieval city walls of Regensburg |
—
|
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: basis for medieval city walls of Regensburg | Statement: [Castra Regina, hasSubsequentUse, basis for medieval city walls of Regensburg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubsequentUse Context triple: [Castra Regina, hasSubsequentUse, basis for medieval city walls of Regensburg]
-
A.
subsequentUse
chosen
Indicates that one entity is used, applied, or consumed after another entity in time or sequence.
-
B.
hasFormerUse
Indicates that something previously served a particular function or role that it no longer has.
-
C.
hasSubsequent
Indicates that one entity occurs, appears, or is positioned after another in a defined sequence or order.
-
D.
usedBefore
Indicates that one entity was utilized or applied prior to the use or occurrence of another entity.
-
E.
hasPresentUse
Indicates that an entity is currently being used or serving a particular function at the present time.
- 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_69e25d1de32c8190a907afe9c3d6cd6d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c888c13c8190b85d2cd425ee84dc |
completed | April 29, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:09 p.m.