Triple
T28003049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Young Man Luther |
E707196
|
entity |
| Predicate | historicalFigurePortrayedAs |
P55200
|
FINISHED |
| Object | agent of religious reform |
—
|
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: agent of religious reform | Statement: [Young Man Luther, historicalFigurePortrayedAs, agent of religious reform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalFigurePortrayedAs Context triple: [Young Man Luther, historicalFigurePortrayedAs, agent of religious reform]
-
A.
wasPortrayedAs
chosen
Indicates that one entity has been depicted or represented in the form or role of another entity, typically within some medium or context.
-
B.
basedOnHistoricalFigure
Indicates that something is derived from, inspired by, or modeled after a real historical person.
-
C.
notableDepictionBy
Indicates that an entity is significantly portrayed or represented by a particular creator, work, or medium.
-
D.
historicalFigure
Indicates that an entity is recognized as a notable person from the past who played a significant role in history.
-
E.
sameHistoricalFigureAs
Indicates that two entities refer to the same historical person, treating them as different representations or records of one individual.
- 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_69ef96b980d88190a753b2f9a978595a |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fdbaa226708190b8ed96e93aad38de |
completed | May 8, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69fdb58b07e48190837e00966de050d4 |
completed | May 8, 2026, 10:06 a.m. |
Created at: April 27, 2026, 7:58 p.m.