Triple
T13422600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lieutenant Governor |
E313393
|
entity |
| Predicate | mayHaveLegislativeRole |
P4024
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lieutenant Governor, mayHaveLegislativeRole, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayHaveLegislativeRole Context triple: [Lieutenant Governor, mayHaveLegislativeRole, yes]
-
A.
legislativeRole
chosen
Indicates that an entity holds or performs a specific official position, function, or duty within a legislative body or lawmaking process.
-
B.
hasPoliticalRole
Indicates that an entity holds, has held, or is assigned a specific political office, function, or position in relation to another entity or context.
-
C.
hasNotablePoliticalRoleIn
Indicates that an entity holds or has held a significant political position, function, or influence within a specified context or jurisdiction.
-
D.
hasPoliticalPositionOn
Indicates that an entity holds or expresses a specific stance, view, or opinion regarding a political issue, policy, or topic.
-
E.
roleInCongress
Indicates the specific position or function an individual holds within a legislative congress.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaecf13748190ae40c7b95164f914 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:39 p.m.