Triple
T21828618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deb Dobkins |
E538924
|
entity |
| Predicate | retainsMemoriesOf |
P145824
|
FINISHED |
| Object | Deb Dobkins's life |
—
|
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: Deb Dobkins's life | Statement: [Deb Dobkins, retainsMemoriesOf, Deb Dobkins's life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: retainsMemoriesOf Context triple: [Deb Dobkins, retainsMemoriesOf, Deb Dobkins's life]
-
A.
rememberedThrough
Indicates that one entity is remembered, commemorated, or kept in memory by means of, or through the influence of, another entity or medium.
-
B.
rememberedFor
Indicates that one entity is known or recognized primarily because of, or in association with, another entity or achievement.
-
C.
erasesMemoriesOf
Indicates that one entity causes the memories of another entity to be removed or wiped out.
-
D.
memorizedBy
Indicates that some content, information, or material has been learned and retained in memory by a particular entity.
-
E.
builtInMemoryOf
Indicates that something was constructed as a tribute or commemoration to a particular person, group, or event.
- 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_69e0c475cda88190987d08f23caebdc1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f091344c848190b1675432a8c255f2 |
completed | April 28, 2026, 10:51 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
| PDg | Predicate description generation | batch_69e6c670ee608190b9cfdc09de74f0de |
completed | April 21, 2026, 12:36 a.m. |
Created at: April 16, 2026, 6:54 p.m.