Triple
T13540984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CC Bloom |
E323383
|
entity |
| Predicate | relationshipDynamicWithHillaryWhitney |
P110765
|
FINISHED |
| Object | contrasting personalities |
—
|
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: contrasting personalities | Statement: [CC Bloom, relationshipDynamicWithHillaryWhitney, contrasting personalities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipDynamicWithHillaryWhitney Context triple: [CC Bloom, relationshipDynamicWithHillaryWhitney, contrasting personalities]
-
A.
relationshipDynamicWithStaceyColbert
Indicates a changing or evolving interpersonal relationship involving Stacey Colbert.
-
B.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
C.
relationshipToHollyGolightly
Indicates the nature or type of relationship an entity has with Holly Golightly.
-
D.
relationshipStatusWithHoward
Indicates the type or state of the relationship an entity currently has with Howard.
-
E.
relationshipWithBlondie
Indicates that there exists some form of relationship or connection between an entity and Blondie.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafd8ba10819098faadcc6adf251e |
completed | April 12, 2026, 2:44 p.m. |
| PD | Predicate disambiguation | batch_69dbae1046c48190b4ee98c6c9cb9d85 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaecc98cc8190829f5be759c4f1e3 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:45 p.m.