Triple
T10006723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McAfee-Maggart |
E198271
|
entity |
| Predicate | bearerProfession |
P35550
|
FINISHED |
| Object | singer-songwriter |
—
|
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: singer-songwriter | Statement: [McAfee-Maggart, bearerProfession, singer-songwriter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bearerProfession Context triple: [McAfee-Maggart, bearerProfession, singer-songwriter]
-
A.
конфессия
Indicates that an entity is associated with, belongs to, or is characterized by a particular religious denomination or confession.
-
B.
isAssociatedWithProfessionOfBearer
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
C.
memberProfession
chosen
Indicates that a member or individual holds or practices a particular profession or occupation.
-
D.
portraysProfession
Indicates that one entity depicts or represents another entity in a specific profession or occupational role.
-
E.
includesProfession
Indicates that one entity’s set of attributes, roles, or members contains a specific profession as part of it.
- 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_69ca830fcca48190bbbd9b20c233835f |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd16afb481909a5d5893e024683f |
completed | April 2, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69cd1da2cf9081908a6c0eb5247d0bc2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:52 p.m.