Triple
T18283158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashildr |
E437912
|
entity |
| Predicate | forgets |
P131172
|
FINISHED |
| Object | much of her long life due to memory limits |
—
|
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: much of her long life due to memory limits | Statement: [Ashildr, forgets, much of her long life due to memory limits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: forgets Context triple: [Ashildr, forgets, much of her long life due to memory limits]
-
A.
erasesMemoriesOf
Indicates that one entity causes the memories of another entity to be removed or wiped out.
-
B.
neglects
Indicates a relationship where one party fails to give appropriate attention, care, or consideration to another party or responsibility.
-
C.
memory
Indicates that an entity retains, recalls, or is associated with stored information or past experiences.
-
D.
attemptedToObliviate
Indicates that one entity tried, but did not necessarily succeed, to erase or alter another entity’s memory.
-
E.
rememberedThrough
Indicates that one entity is remembered, commemorated, or kept in memory by means of, or through the influence of, another entity or medium.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50057c5c881909fcda72f4a98c8c3 |
completed | April 19, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:35 a.m.