Triple
T12081321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catherine Sloper |
E287683
|
entity |
| Predicate | fatherProfession |
P2600
|
FINISHED |
| Object | physician |
—
|
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: physician | Statement: [Catherine Sloper, fatherProfession, physician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatherProfession Context triple: [Catherine Sloper, fatherProfession, physician]
-
A.
fatherOccupation
chosen
Indicates the type of job or profession held by a person's father.
-
B.
fatherPosition
Indicates the spatial or positional relationship occupied by a father relative to another referenced entity or location.
-
C.
familyProfession
Indicates that a person’s profession is shared with or traditionally practiced within their family, reflecting an occupational lineage or family trade.
-
D.
parentOccupation
Indicates that one entity has an occupation which is the job or profession of the other entity’s parent.
-
E.
fatherAffiliation
Indicates that there is an affiliation or organizational association involving a person's father.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bf4f508190842927e7e0642235 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.