Triple
T30710331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laudine, Lady of the Fountain |
E781872
|
entity |
| Predicate | typeOfLady |
P94712
|
FINISHED |
| Object | sovereign lady controlling access to a magical resource |
—
|
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: sovereign lady controlling access to a magical resource | Statement: [Laudine, Lady of the Fountain, typeOfLady, sovereign lady controlling access to a magical resource]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLady Context triple: [Laudine, Lady of the Fountain, typeOfLady, sovereign lady controlling access to a magical resource]
-
A.
relationshipToLady
Indicates the specific type of social, familial, or personal connection that one entity has to a lady.
-
B.
femaleFigure2Attribute
Indicates that a female figure is associated with a particular attribute or characteristic.
-
C.
femaleFigure1Attribute
Indicates that the first female figure possesses or is characterized by a specific attribute.
-
D.
secondLadyTo
Indicates that one person holds the position or role of second lady in relation to another person or office.
-
E.
personType
chosen
Indicates that an entity is classified as a particular type or category of person.
- 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_69f224abfcf081909492e64d3cc35262 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff795d25d08190b7584c72be39d309 |
completed | May 9, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69ff78a90fbc8190a62c57456dc1d4ad |
completed | May 9, 2026, 6:10 p.m. |
Created at: April 29, 2026, 8:35 p.m.