Triple
T22001916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel White |
E543346
|
entity |
| Predicate | relationshipToDarcyRhone |
P146234
|
FINISHED |
| Object | best friend |
—
|
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: best friend | Statement: [Rachel White, relationshipToDarcyRhone, best friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToDarcyRhone Context triple: [Rachel White, relationshipToDarcyRhone, best friend]
-
A.
relationshipToBaudelaires
Indicates the type of personal or familial connection an entity has to the Baudelaires.
-
B.
relationshipToChardonnay
Indicates the specific type of relationship or connection an entity has to Chardonnay, such as production, ownership, use, or association.
-
C.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
D.
relationshipToNickCharles
Indicates a specified type of personal or social relationship that an entity has with Nick Charles.
-
E.
relationshipTypeWithEugénieGrandet
Indicates the specific nature or category of relationship an entity has with Eugénie Grandet.
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1276bf2a48190910d9c27f1c5e74f |
completed | April 28, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e6f62dc9d88190ae387f145f9528de |
completed | April 21, 2026, 3:59 a.m. |
| PDg | Predicate description generation | batch_69e6fad4a540819096cdd5ea08527220 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 8:20 p.m.