Triple
T11027196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louvenia Breedlove |
E260656
|
entity |
| Predicate | relativeTypeToMadamCJKWalker |
P97357
|
FINISHED |
| Object | sister |
—
|
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: sister | Statement: [Louvenia Breedlove, relativeTypeToMadamCJKWalker, sister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeTypeToMadamCJKWalker Context triple: [Louvenia Breedlove, relativeTypeToMadamCJKWalker, sister]
-
A.
isEldestSisterOf
Indicates that one person is the oldest female sibling in relation to another person.
-
B.
pairedTraditionalName
Indicates that two entities are associated as a traditional name pair, typically used together or in customary combination within a cultural or naming convention.
-
C.
relationToNurJahan
Indicates a relationship or connection that an entity has specifically to Nur Jahan.
-
D.
eraAsEmpress
Indicates the time period during which a person held the role or status of empress.
-
E.
Xiaoerjing
Indicates a relationship where something is written, represented, or transcribed using the Xiaoerjing (Arabic-based) script for Sinitic languages.
- F. None of above. chosen
Provenance (4 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797d190f08190bcb5949ee24306f1 |
completed | April 9, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69d7440087ac8190aef2e6f6b13b2635 |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750c99f9881908ee2b01b6ce4b3a1 |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:25 p.m.