Triple
T26646320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betty Schaefer |
E668918
|
entity |
| Predicate | relationshipContrastWith |
P108840
|
FINISHED |
| Object | Norma Desmond |
—
|
NE NERFINISHED |
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: Norma Desmond | Statement: [Betty Schaefer, relationshipContrastWith, Norma Desmond]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipContrastWith Context triple: [Betty Schaefer, relationshipContrastWith, Norma Desmond]
-
A.
hasContrastingRelationshipWith
chosen
Indicates a relationship in which two entities are opposed, divergent, or markedly different in qualities, roles, or effects.
-
B.
relationshipImpact
Indicates how one entity’s relationship with another affects or changes those entities or their interaction.
-
C.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
D.
relationshipToRelative
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
E.
relationshipFocus
Indicates a relationship where particular attention, priority, or emphasis is placed on the connection between two or more entities.
- 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_69ee9d00eb5481908d6c6d0ada2f0c9a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69feaa483fcc81909d8a46b38a8717bf |
completed | May 9, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69fea8c9d45c81908ccc8619e5fefac1 |
completed | May 9, 2026, 3:23 a.m. |
Created at: April 27, 2026, 2:31 a.m.