Triple
T34279036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noble Wimberly Jones |
E879540
|
entity |
| Predicate | colonyRepresented |
P64552
|
FINISHED |
| Object | Province of Georgia |
—
|
NE NERFINISHED |
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: Province of Georgia | Statement: [Noble Wimberly Jones, colonyRepresented, Province of Georgia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colonyRepresented Context triple: [Noble Wimberly Jones, colonyRepresented, Province of Georgia]
-
A.
numberOfColoniesRepresented
Indicates the count of distinct colonies that are represented or involved in relation to a given entity or context.
-
B.
colonyOf
Indicates that one entity is a colony belonging to, founded by, or politically dependent on another entity.
-
C.
colonyNotRepresented
Indicates that a colony lacks official representation in a governing or decision-making body.
-
D.
representedColony
chosen
Indicates that an entity acted as an official representative or delegate for a particular colony in some context or event.
-
E.
countyRepresented
Indicates that a person or representative serves as the official representative for a particular county in a governing or organizational context.
- 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_69f349b5f6648190b9420d94a4cd16e0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71c35327c8190884f1bfe12bd2cd7 |
completed | May 3, 2026, 9:58 a.m. |
| PD | Predicate disambiguation | batch_69f71822d0e88190ac9731c7ae5a4def |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 1:57 a.m.