Triple
T3203055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Guinevere |
E67095
|
entity |
| Predicate | religionOrMythology |
P9595
|
FINISHED |
| Object | medieval Christian romance tradition |
—
|
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: medieval Christian romance tradition | Statement: [Queen Guinevere, religionOrMythology, medieval Christian romance tradition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religionOrMythology Context triple: [Queen Guinevere, religionOrMythology, medieval Christian romance tradition]
-
A.
otherDeity
Indicates that one deity is distinct from and not identical to another deity within a given context or system.
-
B.
linkedToMythology
chosen
Indicates that something has a connection or association with a mythological tradition, figure, story, or theme.
-
C.
religiousTraditions
Indicates a relationship where certain religious customs, practices, or belief systems are associated with or observed by an entity.
-
D.
otherReligion
Indicates that one entity follows or is associated with a religion that is different from the religion of another entity.
-
E.
typeOfDeity
Indicates that one entity is classified as a specific kind or category of deity in relation to another.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada9b188a88190b7b5e9b3be9410db |
completed | March 8, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69ad9e078f7c8190813d9fcb4f5071fb |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.