Triple
T21202090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belogorsky Fortress |
E522478
|
entity |
| Predicate | mediumOfWorkFeaturing |
P99077
|
FINISHED |
| Object | prose |
—
|
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: prose | Statement: [Belogorsky Fortress, mediumOfWorkFeaturing, prose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediumOfWorkFeaturing Context triple: [Belogorsky Fortress, mediumOfWorkFeaturing, prose]
-
A.
mediumOfWorkAppearsIn
chosen
Indicates that a particular medium or format is the form in which a work is presented or appears.
-
B.
mediumDepictedIn
Indicates that a particular medium or material is represented, shown, or referenced within another work or depiction.
-
C.
mediumIncludes
Indicates that a given medium contains, encompasses, or incorporates another item, component, or element within it.
-
D.
mediumCategory
Indicates the classification of an item or content according to the type or form of medium it belongs to (e.g., print, digital, audio, video).
-
E.
mediumOfFame
Indicates the medium, field, or domain through which an entity became famous or gained public recognition.
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73431973c81908c8682d7808a9d13 |
completed | April 21, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69e5f6094e3c81909ee9699e00d371f7 |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:18 p.m.