Triple
T28724232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giant’s Hall |
E730177
|
entity |
| Predicate | locatedWithinSectionOf |
P94409
|
FINISHED |
| Object | main representational tract of Dresden Castle |
—
|
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: main representational tract of Dresden Castle | Statement: [Giant’s Hall, locatedWithinSectionOf, main representational tract of Dresden Castle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedWithinSectionOf Context triple: [Giant’s Hall, locatedWithinSectionOf, main representational tract of Dresden Castle]
-
A.
usesSectionOf
Indicates that one entity makes use of a specific section or part of another entity.
-
B.
isOnSectionOf
Indicates that one entity is located on, or positioned along, a specific segment or subsection of another entity.
-
C.
locationOfTypeSection
Indicates that a particular location is designated as the section or area associated with a specific type or category.
-
D.
appliesToSectionOf
Indicates that something is relevant or applicable specifically to a particular section or subsection of a larger whole.
-
E.
locatedInSectionOfBuilding
chosen
Indicates that one entity is situated within a specific section or area of a building.
- 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_69f043e91fe48190b73bcd8e08d433e0 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69ff9d9cb4f8819083682be3c483b599 |
completed | May 9, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69ff9c38bf9c8190bbb85b32f3ae3d2e |
completed | May 9, 2026, 8:42 p.m. |
Created at: April 28, 2026, 5:55 a.m.