Triple
T6531393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady of Terror |
E152237
|
entity |
| Predicate | partOfMythology |
P9595
|
FINISHED |
| Object | Sekhmet myths of slaughtering humanity |
—
|
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: Sekhmet myths of slaughtering humanity | Statement: [Lady of Terror, partOfMythology, Sekhmet myths of slaughtering humanity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfMythology Context triple: [Lady of Terror, partOfMythology, Sekhmet myths of slaughtering humanity]
-
A.
mythologicalCategory
Indicates that one entity is classified as belonging to the mythological type, group, or category represented by the other entity.
-
B.
linkedToMythology
chosen
Indicates that something has a connection or association with a mythological tradition, figure, story, or theme.
-
C.
mythologicalRole
Indicates the specific function, duty, or status an entity holds within a mythological or legendary context.
-
D.
expandsMythologyOf
Indicates that one entity broadens, enriches, or adds new elements to the mythological background or lore associated with another entity.
-
E.
languageOfMyths
Indicates that the subject is the language in which the myths associated with the object are told or recorded.
- 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_69c688048ec8819093a47f7d332e12ec |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6adbcf820819097ca33a5fc14fd64 |
completed | March 27, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69c68abd9c7c819099e4fe8097cd1b28 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:46 p.m.