Triple
T5460913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazilian government |
E122590
|
entity |
| Predicate | numberOfFederalDistricts |
P1679
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Brazilian government, numberOfFederalDistricts, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFederalDistricts Context triple: [Brazilian government, numberOfFederalDistricts, 1]
-
A.
federalDistrictNumber
Indicates the specific numbered federal electoral or administrative district associated with an entity.
-
B.
numberOfDistricts
chosen
Indicates the total count of districts associated with a given entity or area.
-
C.
includesFederalDistrict
Indicates that one administrative or geographic entity contains or encompasses a federal district within its boundaries.
-
D.
federalDistrictArea
Indicates the total geographic area covered by a federal district.
-
E.
federalDistrictComponent
Indicates that one administrative or territorial unit is a constituent part of a federal district within a federal system.
- 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_69bd4643f16081908d7f29e08096115a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a0d96c8190bd1299edbf764bbb |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:08 p.m.