Triple
T603695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Winthrop |
E11549
|
entity |
| Predicate | numberOfTermsAsGovernor |
P17900
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [John Winthrop, numberOfTermsAsGovernor, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTermsAsGovernor Context triple: [John Winthrop, numberOfTermsAsGovernor, 12]
-
A.
numberOfGovernors
Indicates the total count of governors associated with or governing a specified entity.
-
B.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
C.
numberOfSenators
Indicates the total count of senators associated with a given political body, region, or entity.
-
D.
notableGovernor
Indicates that an individual has served as a governor in a way considered historically or socially significant.
-
E.
numberOfCabinetMembers
Indicates the total count of cabinet members associated with a given government, administration, or leader.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e574444819087999404f3e3ffd9 |
completed | March 1, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69a49cf701e08190966d06b9ff4b582b |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49e55b2248190b0ae3d692c0fa143 |
completed | March 1, 2026, 8:15 p.m. |
Created at: March 1, 2026, 7:35 p.m.