Triple
T121435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alaska State Legislature |
E2451
|
entity |
| Predicate | meetsInRegularSession |
P1309
|
FINISHED |
| Object | annually |
—
|
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: annually | Statement: [Alaska State Legislature, meetsInRegularSession, annually]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meetsInRegularSession Context triple: [Alaska State Legislature, meetsInRegularSession, annually]
-
A.
convenesRegularSession
chosen
Indicates that an entity formally brings together a group or body for its routine or scheduled meeting.
-
B.
meetsEvery
Indicates that one entity encounters or comes into contact with every member of a specified set of entities.
-
C.
meetsDuring
Indicates that one entity encounters or comes together with another while a specified event or time interval is in progress.
-
D.
meetsAs
Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
-
E.
convenesIn
Indicates that an entity brings together or assembles a group, meeting, or event at a specific place or venue.
- 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a258fd278481908ad4498e03f38e2f |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a25647fe6081908cb0405266d35ff5 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.