Triple
T2699776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lieutenant Governor of Massachusetts |
E59201
|
entity |
| Predicate | officeClassification |
P14964
|
FINISHED |
| Object | state constitutional office |
—
|
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: state constitutional office | Statement: [Lieutenant Governor of Massachusetts, officeClassification, state constitutional office]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeClassification Context triple: [Lieutenant Governor of Massachusetts, officeClassification, state constitutional office]
-
A.
officeCategory
chosen
Indicates the classification or type of an office within a defined categorization scheme.
-
B.
officeTerm
Indicates the period of time during which an individual officially holds a particular position or office.
-
C.
office
Indicates that an entity holds or occupies an official position, role, or post within an organization or institution.
-
D.
otherOffice
Indicates that one office is an alternative or additional office associated with the same organization, person, or entity as another office.
-
E.
officeItAbbreviatesRole
Indicates that an office title or designation serves as an abbreviation for a particular role or position.
- 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_69ab4ac66bc88190b9e4afa5fc843f72 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda34ba508190be8e2c9e4052adfc |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd82062988190b4292f242ad70b2c |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.