Triple
T6606255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Virgin’s Fountain |
E149125
|
entity |
| Predicate | hasAssociatedLegend |
P1582
|
FINISHED |
| Object | Mary’s daily visits to draw water |
—
|
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: Mary’s daily visits to draw water | Statement: [The Virgin’s Fountain, hasAssociatedLegend, Mary’s daily visits to draw water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedLegend Context triple: [The Virgin’s Fountain, hasAssociatedLegend, Mary’s daily visits to draw water]
-
A.
hasLegendAssociatedWith
chosen
Indicates that something is connected to or accompanied by a traditional story, myth, or legend.
-
B.
instrumentInLegend
Indicates that an instrument is featured or plays a role within a legend or mythological narrative.
-
C.
hasAssociatedPosition
Indicates that one entity is linked to a specific role, job, or spatial/organizational position associated with it.
-
D.
hasLabel
Indicates that an entity is associated with a specific textual label or name used to identify or describe it.
-
E.
hasKeyFigure
Indicates that an entity includes, involves, or is characterized by an important or central person relevant to it.
- 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_69c687eaa7508190bb58ce2aa02039b3 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6acfd17388190bd0bb8b2371e7df1 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:57 p.m.