Triple
T1090254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senate of the Republic (Mexico) |
E24145
|
entity |
| Predicate | seatsPerState |
P2838
|
FINISHED |
| Object | 3 elected senators per state and Mexico City |
—
|
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: 3 elected senators per state and Mexico City | Statement: [Senate of the Republic (Mexico), seatsPerState, 3 elected senators per state and Mexico City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatsPerState Context triple: [Senate of the Republic (Mexico), seatsPerState, 3 elected senators per state and Mexico City]
-
A.
numberOfStatesRepresented
Indicates how many distinct states are represented or covered in a given context or entity.
-
B.
seatOfElector
Indicates the location or jurisdiction that serves as the official base or constituency of a given elector.
-
C.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
D.
numberOfStates
Indicates the total count of distinct states or conditions associated with an entity or system.
-
E.
hasMembersPerState
chosen
Indicates a relationship that specifies how many members are associated with each state.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b980c8448190b08c3a9a7e7f4e85 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b741b0cc8190be001a16a81f6d9e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.