Triple
T35072742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | An Only Child |
E1011924
|
entity |
| Predicate | hasAuthorOccupationOfProtagonist |
P21567
|
FINISHED |
| Object | writer |
—
|
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: writer | Statement: [An Only Child, hasAuthorOccupationOfProtagonist, writer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAuthorOccupationOfProtagonist Context triple: [An Only Child, hasAuthorOccupationOfProtagonist, writer]
-
A.
hasAuthorOccupationOfAuthor
Indicates that an author has a specific occupation or professional role.
-
B.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
-
C.
otherProtagonistOccupation
Indicates that another main character in the narrative has a specific occupation or job role.
-
D.
protagonistParentOccupation
Indicates the occupation or job held by the protagonist’s parent in the described context.
-
E.
featuresProtagonistOccupation
chosen
Indicates that the work’s main character has a specified occupation or job role.
- 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_69f76dd193108190af2528186f25b72a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: May 3, 2026, 4:01 p.m.