Triple
T18107687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hohe Dock |
E433385
|
entity |
| Predicate | hasParentArea |
P47433
|
FINISHED |
| Object | district of Zell am See |
—
|
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: district of Zell am See | Statement: [Hohe Dock, hasParentArea, district of Zell am See]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParentArea Context triple: [Hohe Dock, hasParentArea, district of Zell am See]
-
A.
hasChildrenArea
Indicates that an entity includes or is associated with a designated area intended for children.
-
B.
hasParentUnit
chosen
Indicates that one unit is hierarchically contained within or belongs to another, higher-level unit.
-
C.
hasParentCode
Indicates that an entity is associated with a parent code from which it is derived or to which it is hierarchically linked.
-
D.
hasParentSubdivisionSet
Indicates that an entity is associated with a set of higher-level subdivisions to which it belongs or from which it is derived.
-
E.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddbb3d408190b5fc7870bc6512f4 |
completed | April 19, 2026, 1:50 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:28 a.m.