Triple
T34780748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hester |
E1002651
|
entity |
| Predicate | emotionalRelationToChild |
P166245
|
FINISHED |
| Object | lack of genuine affection for Paul |
—
|
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: lack of genuine affection for Paul | Statement: [Hester, emotionalRelationToChild, lack of genuine affection for Paul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalRelationToChild Context triple: [Hester, emotionalRelationToChild, lack of genuine affection for Paul]
-
A.
emotionallyAttachedTo
Indicates that one entity has a strong emotional bond, affection, or dependence directed toward another entity.
-
B.
relationshipToMother
Indicates the specific familial or social connection an entity has to its mother.
-
C.
relationshipToParents
Indicates the type or nature of a person's familial relationship to their parents.
-
D.
attitudeTowardDependents
chosen
Indicates the nature or quality of an entity’s feelings, stance, or behavior toward those who depend on it.
-
E.
emotionalToneOfRelationshipWithTheodore
Indicates the overall emotional quality or tone characterizing an entity’s relationship with Theodore.
- 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.