Triple
T317006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Massachusetts Senate |
E7728
|
entity |
| Predicate | openMeetingsRequirement |
P11970
|
FINISHED |
| Object | subject to Massachusetts open meeting laws |
—
|
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: subject to Massachusetts open meeting laws | Statement: [Massachusetts Senate, openMeetingsRequirement, subject to Massachusetts open meeting laws]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openMeetingsRequirement Context triple: [Massachusetts Senate, openMeetingsRequirement, subject to Massachusetts open meeting laws]
-
A.
meetingType
Indicates the specific category or format of a meeting that characterizes how it is organized or conducted.
-
B.
hasPrimaryMeeting
Indicates that an entity is associated with its main or most important meeting, distinguishing it from other meetings it may have.
-
C.
meetsBy
Indicates that one entity encounters or comes together with another entity, typically at a specific time or place.
-
D.
meets
Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
-
E.
meetsAs
Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea65ca7081908093e6aaaf2d34f7 |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e943f12c8190883854aeed974260 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea08878c8190a5e8a90f620a3888 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.