Triple
T696830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luitpoldhain |
E13911
|
entity |
| Predicate | hasTypeOfArea |
P6822
|
FINISHED |
| Object | recreational area |
—
|
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: recreational area | Statement: [Luitpoldhain, hasTypeOfArea, recreational area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfArea Context triple: [Luitpoldhain, hasTypeOfArea, recreational area]
-
A.
hasAreaType
chosen
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
B.
hasAreaCodeType
Indicates that an entity’s area code is associated with a specific type or classification of area code.
-
C.
hasResidentialArea
Indicates that an entity includes, contains, or is associated with an area designated for people to live or reside.
-
D.
hasCoreArea
Indicates that an entity possesses a primary or central area that is fundamental to its structure, function, or focus.
-
E.
hasFacilityType
Indicates that an entity possesses or is associated with a specific type or category of facility.
- 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_69a493406c408190957eeec9048a8fb6 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a0c8055881909565ebde2be8fd7a |
completed | March 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69a49d2586b081908e052cc5ba1d2685 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.