Triple
T3628859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senate of Trinidad and Tobago |
E76904
|
entity |
| Predicate | numberOfGovernmentSenators |
P49647
|
FINISHED |
| Object | 16 |
—
|
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: 16 | Statement: [Senate of Trinidad and Tobago, numberOfGovernmentSenators, 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGovernmentSenators Context triple: [Senate of Trinidad and Tobago, numberOfGovernmentSenators, 16]
-
A.
numberOfSenators
Indicates the total count of senators associated with a given political body, region, or entity.
-
B.
numberOfSenates
Indicates the total count of senate bodies associated with or present in a given context or entity.
-
C.
numberOfSeatsInSenate
Indicates the total count of seats allocated in a given senate.
-
D.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
E.
totalNumberOfLegislators
Indicates the total count of legislators associated with a given political body, jurisdiction, or legislative session.
- F. None of above. chosen
Provenance (4 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_69ad85dc03948190b35b7189e4175bcc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc2df2b708190afef6925a53ec551 |
completed | March 8, 2026, 6:41 p.m. |
| PD | Predicate disambiguation | batch_69adb8410a5881909c94818d7060b2b0 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb902e61c81908f10494f828e260f |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:23 p.m.