Triple
T34839011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stiftskirche Tübingen |
E1004281
|
entity |
| Predicate | mediaTypeOfDepicted |
P17824
|
FINISHED |
| Object | church |
—
|
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: church | Statement: [Stiftskirche Tübingen, mediaTypeOfDepicted, church]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaTypeOfDepicted Context triple: [Stiftskirche Tübingen, mediaTypeOfDepicted, church]
-
A.
mediaType
Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
-
B.
mediaDepictionAs
chosen
Indicates that one entity is portrayed or represented as another entity or in a particular way within some medium (e.g., image, film, text).
-
C.
primaryMediumOfDepiction
Indicates that a specified medium (such as painting, sculpture, or photography) is the main form through which an entity is depicted.
-
D.
depictsMedium
Indicates that one entity visually represents or portrays the medium or material of another entity.
-
E.
mediaTypeExample
Indicates that something serves as an example or illustrative instance of a particular media type.
- 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_69f76db97714819099b5bed36fd64e9d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4 p.m.