Triple
T13956249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurt Diemberger |
E335666
|
entity |
| Predicate | amputations |
P53592
|
FINISHED |
| Object | parts of both legs below the knee |
—
|
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: parts of both legs below the knee | Statement: [Kurt Diemberger, amputations, parts of both legs below the knee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: amputations Context triple: [Kurt Diemberger, amputations, parts of both legs below the knee]
-
A.
lostLimb
chosen
Indicates that an entity has had one or more of its limbs removed or rendered permanently absent, typically as a result of injury, surgery, or trauma.
-
B.
lostLimbTo
Indicates that one entity has had a limb removed, severed, or rendered nonfunctional as a direct result of another entity or cause.
-
C.
appendages
Indicates that one entity has limbs or projecting body parts that are attached to another entity.
-
D.
numberOfLegsLost
Indicates the number of legs an entity has lost as a result of some event or condition.
-
E.
hasProsthesis
Indicates that an entity possesses or is equipped with an artificial substitute for a missing or impaired body part.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e78a4a481908e438745631a43c0 |
completed | April 14, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69de05a3ccf88190b45c742db483fa08 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:17 p.m.