Triple
T13518096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosa Hubermann |
E322819
|
entity |
| Predicate | relationshipToLieselMeminger |
P110077
|
FINISHED |
| Object | foster mother |
—
|
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: foster mother | Statement: [Rosa Hubermann, relationshipToLieselMeminger, foster mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToLieselMeminger Context triple: [Rosa Hubermann, relationshipToLieselMeminger, foster mother]
-
A.
relationshipToHuckFinn
Indicates the specific type of personal or social relationship an entity has to Huck Finn.
-
B.
relationshipToBenjy
Indicates the specific type of relationship or connection an entity has to Benjy.
-
C.
relationshipToHenry
Indicates the specific type of relationship or connection that an entity has to Henry.
-
D.
relationshipToJoadFamily
Indicates the specific familial or social connection an entity has with members of the Joad family.
-
E.
relationshipToAuntEller
Indicates the specific familial relationship that an entity has to Aunt Eller (e.g., whether and how they are related to her).
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa27f048190bed33a98e28c8d09 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
| PDg | Predicate description generation | batch_69dbaee128d88190b097be17fdd2f92b |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:44 p.m.