Triple
T3090461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heinrich Marx |
E64467
|
entity |
| Predicate | reasonForConversion |
P45854
|
FINISHED |
| Object | to continue legal career under Prussian law |
—
|
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: to continue legal career under Prussian law | Statement: [Heinrich Marx, reasonForConversion, to continue legal career under Prussian law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForConversion Context triple: [Heinrich Marx, reasonForConversion, to continue legal career under Prussian law]
-
A.
reasonForChange
Indicates that one entity serves as the cause, justification, or motivation for a modification or change in another entity or state.
-
B.
reasonForUse
Indicates that one entity specifies the justification, purpose, or motivation for using another entity.
-
C.
statedReason
Indicates that one entity expresses or provides another entity as the explanation, justification, or motive for an action, event, or claim.
-
D.
selectionReason
Indicates the reason or justification for choosing or selecting one entity over alternatives.
-
E.
placeOfConversion
Indicates the location where an entity undergoes a religious, ideological, or formal conversion.
- F. None of above. chosen
Provenance (4 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_69ad857c97d88190b26f9b1c90839c77 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada20d8f788190b05b8b6b5042bc1a |
completed | March 8, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69ad9ded78f881908be6fc0fb7c35764 |
completed | March 8, 2026, 4:03 p.m. |
| PDg | Predicate description generation | batch_69ada0f6fef48190b13898be383a246b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:03 p.m.