Triple
T19729607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Spaulding |
E473816
|
entity |
| Predicate | relationshipToDouglasSpaulding |
P137108
|
FINISHED |
| Object | younger brother |
—
|
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: younger brother | Statement: [Tom Spaulding, relationshipToDouglasSpaulding, younger brother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToDouglasSpaulding Context triple: [Tom Spaulding, relationshipToDouglasSpaulding, younger brother]
-
A.
relationshipTypeWithEdwardDouglas
Indicates the specific nature or category of relationship that an entity has with Edward Douglas.
-
B.
relationshipToDickieWinslow
Indicates the specific type of relationship or connection an entity has to Dickie Winslow.
-
C.
John Thornton Kirkland
Indicates a naming relationship where the label or identifier "John Thornton Kirkland" is assigned to a specific individual.
-
D.
relationshipToStanley
Indicates the specific type of personal or social relationship an entity has with Stanley.
-
E.
relationshipTypeWithDauberDybinski
Indicates a specific type of relationship or association that exists between an entity and Dauber Dybinski.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649fb27c48190893bfbc1018f12e2 |
completed | April 20, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:47 p.m.