Triple
T1617984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senate of Argentina |
E34762
|
entity |
| Predicate | numberOfSenatorsForBuenosAiresCity |
P4272
|
FINISHED |
| Object | 3 |
—
|
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 | Statement: [Senate of Argentina, numberOfSenatorsForBuenosAiresCity, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSenatorsForBuenosAiresCity Context triple: [Senate of Argentina, numberOfSenatorsForBuenosAiresCity, 3]
-
A.
numberOfSenators
chosen
Indicates the total count of senators associated with a given political body, region, or entity.
-
B.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
C.
representedInSenate
Indicates that an entity serves as a representative for another entity within a senate or upper legislative chamber.
-
D.
hasUSSenator
Indicates that a specified state or jurisdiction is represented by a particular individual serving as a United States Senator.
-
E.
senatorsServeAt
Indicates that certain individuals hold and perform the official duties of senators within a particular governing body or jurisdiction.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93fef600c819080fe75c42c8e6dac |
completed | March 5, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69a907c52a548190b648a31ea306dd5b |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.