Triple
T29195949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catherine Knight |
E740122
|
entity |
| Predicate | legalRelationship |
P165389
|
FINISHED |
| Object | adoptive mother of Edward Austen Knight |
—
|
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: adoptive mother of Edward Austen Knight | Statement: [Catherine Knight, legalRelationship, adoptive mother of Edward Austen Knight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalRelationship Context triple: [Catherine Knight, legalRelationship, adoptive mother of Edward Austen Knight]
-
A.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
courtRelationship
chosen
Indicates a formal legal relationship between parties established or recognized through court proceedings or judicial decisions.
-
C.
addressesRelationship
Indicates that one entity directs communication, remarks, or attention specifically toward another entity.
-
D.
coversRelationship
Indicates that one entity extends over, includes, or provides encompassing coverage for another entity or set of entities.
-
E.
reportsRelationship
Indicates that one entity formally provides information, findings, or status about another entity or situation.
- 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_69f07cb8033c8190b8807e219a14333d |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fd64bc86848190a49f451a8fc5cf1e |
completed | May 8, 2026, 4:21 a.m. |
| PD | Predicate disambiguation | batch_69fd5ff4a648819090756d90fd195d9a |
completed | May 8, 2026, 4 a.m. |
Created at: April 28, 2026, 12:04 p.m.