Triple
T3001614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gog of the land of Magog |
E81799
|
entity |
| Predicate | textualCategory |
P5468
|
FINISHED |
| Object | prophetic literature |
—
|
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: prophetic literature | Statement: [Gog of the land of Magog, textualCategory, prophetic literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textualCategory Context triple: [Gog of the land of Magog, textualCategory, prophetic literature]
-
A.
textType
chosen
Indicates the classification of a text according to its type, format, or genre.
-
B.
canonicalCategory
Indicates that an entity is assigned to its primary or standard category within a classification system.
-
C.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
D.
commonsCategory
Indicates that an entity is associated with a specific media or topic category on Wikimedia Commons.
-
E.
textualStructure
Indicates how parts of a text are organized and related to each other within its overall structure.
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a11b4bc81909ce06121361b4e0f |
completed | March 8, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69ad9615fefc8190ad96da92519cb7a3 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.