Triple
T5467617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | de León |
E122750
|
entity |
| Predicate | hasNotableFieldOfActivity |
P39276
|
FINISHED |
| Object | religious scholarship |
—
|
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: religious scholarship | Statement: [de León, hasNotableFieldOfActivity, religious scholarship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableFieldOfActivity Context triple: [de León, hasNotableFieldOfActivity, religious scholarship]
-
A.
hasNotableProfessionField
Indicates that an entity’s notable profession or occupation belongs to a particular professional field or domain.
-
B.
hasNotableWorkCategory
Indicates that an entity’s notable work belongs to, or is classified under, a particular category or type.
-
C.
notableYearOfActivity
Indicates the specific year during which an entity was particularly active, prominent, or notable in its activities or impact.
-
D.
notableField
chosen
Indicates the field, discipline, or area of activity for which an entity is especially known or distinguished.
-
E.
hasNotableFacultyField
Indicates that an institution’s notable faculty are associated with or specialize in a particular academic or professional field.
- 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_69bd4643f16081908d7f29e08096115a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a370a88190b5d17b8a5387138d |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:09 p.m.