Triple
T416472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senate of Pakistan |
E8003
|
entity |
| Predicate | fractionOfMembersRetiredEachCycle |
P11342
|
FINISHED |
| Object | one half |
—
|
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: one half | Statement: [Senate of Pakistan, fractionOfMembersRetiredEachCycle, one half]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fractionOfMembersRetiredEachCycle Context triple: [Senate of Pakistan, fractionOfMembersRetiredEachCycle, one half]
-
A.
rajyaSabhaMembersRetireFraction
chosen
Indicates the fraction of Rajya Sabha members that retire at the end of each retirement cycle or term interval.
-
B.
retiredNumbersCount
Indicates the number of jersey or identification numbers that have been officially retired from use.
-
C.
retirementPeriod
Indicates the time span during which an entity is considered to be retired or in retirement status.
-
D.
retiredNumber
Indicates that an entity (typically a team or organization) has formally withdrawn a specific number from future use, usually to honor a particular individual or achievement associated with that number.
-
E.
numberOfNonPermanentMembers
Indicates the count of entities that hold non-permanent (temporary or rotating) membership within a larger group or body.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eebde1d881908fb212bfba9d7c67 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd1ca148190a66bd8c5aad867d5 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.