Triple
T30183531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schloss Wolfsgarten |
E767270
|
entity |
| Predicate | isInForest |
P39061
|
FINISHED |
| Object | forest area near Langen |
—
|
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: forest area near Langen | Statement: [Schloss Wolfsgarten, isInForest, forest area near Langen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInForest Context triple: [Schloss Wolfsgarten, isInForest, forest area near Langen]
-
A.
isForested
Indicates that an area or region is covered predominantly by forest or dense tree vegetation.
-
B.
locatedInForest
chosen
Indicates that an entity is situated within the boundaries of a forest.
-
C.
hasNearbyForestType
Indicates that one entity is located close to, or in the vicinity of, a forest of a specified type.
-
D.
hasForestType
Indicates that an area or location is characterized by a specific type or classification of forest.
-
E.
hasNearbyWoodland
Indicates that one entity is located close to or in the immediate vicinity of a woodland area associated with another entity.
- 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_69f2247cc3d88190811dec3face94bf5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67f43c8388190a0fce4ef4e392274 |
completed | May 2, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69f673c7a4588190837854f3ef61e6bf |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 7:26 p.m.