Triple
T2235530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucy Flucker Knox |
E49270
|
entity |
| Predicate | spouseMilitaryRole |
P26554
|
FINISHED |
| Object | Chief of Artillery of the Continental Army |
—
|
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: Chief of Artillery of the Continental Army | Statement: [Lucy Flucker Knox, spouseMilitaryRole, Chief of Artillery of the Continental Army]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseMilitaryRole Context triple: [Lucy Flucker Knox, spouseMilitaryRole, Chief of Artillery of the Continental Army]
-
A.
spouseOccupation
Indicates that one person’s spouse has a particular job, profession, or occupation.
-
B.
spouseOffice
chosen
Indicates that one entity holds an office or position that is associated with, or held by, the spouse of another entity.
-
C.
spouseFamily
Indicates a family relationship formed through marriage, such as between a person and their spouse’s relatives.
-
D.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
-
E.
spouseMemberOf
Indicates that a person’s spouse is a member of a specified group, organization, or entity.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc093ba0c819091df09a0e018fce1 |
completed | March 7, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69abbdafc07881909101266a33ae7031 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.