Triple
T4774814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Congress of Brazil |
E106017
|
entity |
| Predicate | totalNumberOfMembers |
P31691
|
FINISHED |
| Object | 594 |
—
|
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: 594 | Statement: [National Congress of Brazil, totalNumberOfMembers, 594]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalNumberOfMembers Context triple: [National Congress of Brazil, totalNumberOfMembers, 594]
-
A.
numberOfFullMembers
Indicates the total count of entities that hold full membership status within a specified group or organization.
-
B.
originalNumberOfMembers
Indicates the initial total count of members in a group or organization before any changes such as additions or removals.
-
C.
numberOfAssociateMembers
Indicates the total count of associate members linked to a given entity.
-
D.
numberOfGroupMembers
chosen
Indicates the total count of individual members that belong to a specified group.
-
E.
numberOfMembersReturned
Indicates the quantity of members that are provided or yielded as a result of an operation or query.
- 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_69bd43f3074c8190937e7b0a457fe9f1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6584481081908f1041a8827e0b42 |
completed | March 20, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69bd6229d8448190a271719e5e30fd82 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.