Triple
T1856599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New England Confederation |
E41717
|
entity |
| Predicate | numberOfCommissionersPerColony |
P21525
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [New England Confederation, numberOfCommissionersPerColony, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCommissionersPerColony Context triple: [New England Confederation, numberOfCommissionersPerColony, 2]
-
A.
numberOfColonies
Indicates the count of distinct colonies associated with or possessed by a given entity.
-
B.
numberOfCommissioners
chosen
Indicates the specific count of commissioners associated with a given entity or context.
-
C.
numberOfColoniesRepresented
Indicates the count of distinct colonies that are represented or involved in relation to a given entity or context.
-
D.
colonyOf
Indicates that one entity is a colony belonging to, founded by, or politically dependent on another entity.
-
E.
hasNumberOfCouncillors
Indicates the relationship that specifies how many councillors are associated with a given 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_69a8864a83848190a4ec02721306c511 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb231de14819091da3a20ed03c430 |
completed | March 7, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69abafde4598819099d8229128348fd3 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.