Triple
T4036759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudolf of Rheinfelden |
E83844
|
entity |
| Predicate | reasonForLostLimb |
P14656
|
FINISHED |
| Object | severed in battle |
—
|
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: severed in battle | Statement: [Rudolf of Rheinfelden, reasonForLostLimb, severed in battle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForLostLimb Context triple: [Rudolf of Rheinfelden, reasonForLostLimb, severed in battle]
-
A.
numberOfLegsLost
Indicates the number of legs an entity has lost as a result of some event or condition.
-
B.
causeOfDisability
Indicates that one entity is the reason or source that brings about another entity’s disability.
-
C.
causeOfInjury
chosen
Indicates that one entity is the source or reason that another entity sustained an injury.
-
D.
lostWith
Indicates that one entity experienced a loss or defeat in conjunction with, or as part of the same side/team as, another entity.
-
E.
reasonForLossOfVote
Indicates the specific cause or circumstance that led to an entity losing its right or ability to vote.
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb349e648190b9f227df4cd76fa0 |
completed | March 9, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69aef8fe440c819093a7fa22c4ff3f1a |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:36 p.m.