Triple
T31207567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coriantumr |
E795642
|
entity |
| Predicate | woundedSeverely |
P171029
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Coriantumr, woundedSeverely, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: woundedSeverely Context triple: [Coriantumr, woundedSeverely, yes]
-
A.
woundedAt
Indicates that an entity was injured or harmed at a specific place or during a particular event.
-
B.
wasWoundedIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or conflict.
-
C.
casualtiesWounded
Indicates that an event or situation resulted in people being injured but not killed.
-
D.
killedOrMortallyWounded
Indicates that one entity caused the death of, or inflicted injuries certain to result in the death of, another entity.
-
E.
hasApproximateNumberOfWounds
Indicates that an entity has a number of wounds that is known only approximately rather than as an exact count.
- 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_69f224d8c6608190b7882466521f62be |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c24de048190973b05290ff5c404 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f696673214819094350e1d2648ef34 |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f6978ec27c8190a488e1f9c2566d38 |
completed | May 3, 2026, 12:32 a.m. |
Created at: April 29, 2026, 9:09 p.m.