Triple
T38650432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Morton |
E939725
|
entity |
| Predicate | hasFamilyRoleInPlot |
P38221
|
FINISHED |
| Object | mother figure |
—
|
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 figure | Statement: [Mrs. Morton, hasFamilyRoleInPlot, mother figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFamilyRoleInPlot Context triple: [Mrs. Morton, hasFamilyRoleInPlot, mother figure]
-
A.
hasFamilyRole
chosen
Indicates that one entity holds a specific familial role or position in relation to another entity.
-
B.
hasProtagonistFamilyMember
Indicates that a work’s protagonist has a specified individual as a member of their family.
-
C.
hasMainCastFamilyRelationship
Indicates that there is a family relationship between members of the main cast in a work (e.g., film, series, or play).
-
D.
belongsToFamily
Indicates that an entity is a member of, or is associated as part of, a specific family group.
-
E.
hasFictionalFamilyMember
Indicates that one entity has another entity as a family member within a fictional or imagined context.
- 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_69f76ede49648190a48bfe47032a05a3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69feabcda59481908f2bc13b46fcced1 |
completed | May 9, 2026, 3:36 a.m. |
| PD | Predicate disambiguation | batch_69feaabd63f88190b30dcf6dd2ea39d1 |
completed | May 9, 2026, 3:32 a.m. |
Created at: May 3, 2026, 4:33 p.m.