Triple
T31527261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | publication of My Mother’s Keeper in 1985 |
E804379
|
entity |
| Predicate | involvedTheme |
P91427
|
FINISHED |
| Object | mother–daughter conflict |
—
|
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: mother–daughter conflict | Statement: [publication of My Mother’s Keeper in 1985, involvedTheme, mother–daughter conflict]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvedTheme Context triple: [publication of My Mother’s Keeper in 1985, involvedTheme, mother–daughter conflict]
-
A.
tacklesTheme
chosen
Indicates that one entity addresses, explores, or deals with a particular theme as a central subject.
-
B.
thematicConcept
Indicates that one entity embodies, expresses, or is centrally concerned with a particular underlying theme or conceptual idea represented by the other entity.
-
C.
majorThemeAssociation
Indicates that one entity is associated with another as a primary or central theme.
-
D.
notableTheme
Indicates that a particular theme is prominently featured in, or strongly associated with, an entity such as a work, event, or body of content.
-
E.
themeExplores
Indicates that a work, action, or discourse centrally examines, investigates, or delves into a particular theme or subject.
- 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_69f348cf839c81908657048402f7f97b |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd09840ea88190a2e6d7e577ade717 |
completed | May 7, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69fd064c49988190afadddbd04d7cb94 |
completed | May 7, 2026, 9:38 p.m. |
Created at: April 30, 2026, 9:59 p.m.