Triple
T9489127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawthorne family |
E228839
|
entity |
| Predicate | hasNotableOccupation |
P13522
|
FINISHED |
| Object | novelist |
—
|
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: novelist | Statement: [Hawthorne family, hasNotableOccupation, novelist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableOccupation Context triple: [Hawthorne family, hasNotableOccupation, novelist]
-
A.
hasNotableProfessionField
Indicates that an entity’s notable profession or occupation belongs to a particular professional field or domain.
-
B.
hasNotableBearerOccupation
chosen
Indicates that an entity is associated with a notable person who holds a specific occupation.
-
C.
hasNotableProfessionDistributionIn
Indicates that the distribution or prevalence of notable professions associated with an entity is observed or characterized within a specified context, such as a location or group.
-
D.
hasNotablePosition
Indicates that an entity holds or has held a position, role, or office considered notable or significant.
-
E.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
- 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_69ca847424f081908180305555139f7a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd80c5a05c8190b97d34f010e60ca1 |
completed | April 1, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69cca561e6b0819090aa795f3c3a2083 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:55 p.m.