Triple
T22002083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosa Coldfield |
E543350
|
entity |
| Predicate | relationshipToThomasSutpen |
P146236
|
FINISHED |
| Object | former fiancée |
—
|
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: former fiancée | Statement: [Rosa Coldfield, relationshipToThomasSutpen, former fiancée]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToThomasSutpen Context triple: [Rosa Coldfield, relationshipToThomasSutpen, former fiancée]
-
A.
relationshipToMissWatson
Indicates the type or nature of a person's relational connection to Miss Watson (e.g., familial, social, or other defined relationship).
-
B.
relationshipToCarolineCompson
Indicates the specific familial or social relationship that an entity has to Caroline Compson.
-
C.
relationshipToDésirée
Indicates the specific type of personal or social relationship that one entity has to Désirée.
-
D.
relationshipToEdna Pontellier
Indicates the specific personal, familial, or social connection that an entity has to Edna Pontellier.
-
E.
relationshipToBlancheDuBois
Indicates the specific familial, social, or interpersonal connection an entity has with Blanche DuBois.
- 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.