Triple
T29315857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avatar cycle |
E743372
|
entity |
| Predicate | partlySeveredFrom |
P167958
|
FINISHED |
| Object | past Avatars |
—
|
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: past Avatars | Statement: [Avatar cycle, partlySeveredFrom, past Avatars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partlySeveredFrom Context triple: [Avatar cycle, partlySeveredFrom, past Avatars]
-
A.
partlySeveredDuring
Indicates that an entity was only partially cut or separated during a specified event or time interval.
-
B.
partlySeveredBy
chosen
Indicates that one entity is cut, divided, or separated by another entity, but the separation is incomplete or only affects part of it.
-
C.
partlyDismantledBy
Indicates that an entity has been only partially taken apart, removed, or deconstructed by another agent or process.
-
D.
dismembered
Indicates that one entity has cut or torn another entity’s body into separate parts, typically removing limbs or sections.
-
E.
partiallyDestroyed
Indicates that an entity has been damaged or ruined to a significant extent but not completely destroyed.
- 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_69f0912502c8819087d9e8398ee991a8 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 28, 2026, 1:19 p.m.