Triple
T25014433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy Wyman |
E626086
|
entity |
| Predicate | succeededBy (Connecticut Comptroller) |
P162854
|
FINISHED |
| Object | Kevin Lembo |
—
|
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: Kevin Lembo | Statement: [Nancy Wyman, succeededBy (Connecticut Comptroller), Kevin Lembo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: succeededBy (Connecticut Comptroller) Context triple: [Nancy Wyman, succeededBy (Connecticut Comptroller), Kevin Lembo]
-
A.
precededBy (Connecticut Comptroller)
Indicates that one officeholder or term in the role of Connecticut Comptroller came immediately before another in chronological order.
-
B.
succeededBy (Governor of New York)
Indicates that one individual directly follows another in holding the office of Governor of New York.
-
C.
succeededBy (Governor of Vermont)
Indicates that one individual directly followed another in holding the office of Governor of Vermont.
-
D.
succeededBy (Governor of Pennsylvania)
Indicates that one individual directly follows another in holding the office of Governor of Pennsylvania.
-
E.
succeededBy (Governor of Maine)
Indicates that one individual directly follows another in holding the office of Governor of Maine.
- 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_69e2ff27755881908490178e83701160 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f62e83045c8190a424a2e401a88e9e |
completed | May 2, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
| PDg | Predicate description generation | batch_69f62d886828819080ec2f742b9449e3 |
completed | May 2, 2026, 4:59 p.m. |
Created at: April 18, 2026, 6:06 a.m.