Triple
T26715341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Banning |
E673536
|
entity |
| Predicate | hasAmnesiaOf |
P131172
|
FINISHED |
| Object | his life as Peter Pan |
—
|
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: his life as Peter Pan | Statement: [Peter Banning, hasAmnesiaOf, his life as Peter Pan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAmnesiaOf Context triple: [Peter Banning, hasAmnesiaOf, his life as Peter Pan]
-
A.
hasMemoryBlackouts
Indicates that an entity experiences episodes of lost or impaired memory for certain periods or events.
-
B.
erasesMemoriesOf
Indicates that one entity causes the memories of another entity to be removed or wiped out.
-
C.
forgets
chosen
Indicates that an entity fails to remember or loses awareness of something that was previously known or intended.
-
D.
hasArtificialMemories
Indicates that an entity possesses memories that were created or implanted through artificial or non-natural means.
-
E.
memoryDeficit
Indicates a relationship where an entity exhibits an impairment or reduction in its ability to store, retain, or recall information.
- 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_69eecda3a22881908f3061c760b9d542 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f617c35620819092446c9841b1e6c4 |
completed | May 2, 2026, 3:26 p.m. |
| PD | Predicate disambiguation | batch_69f60b8dfa0c8190864e1a940024d0a0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 3:37 a.m.