Triple
T264432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parliament of Pakistan |
E5693
|
entity |
| Predicate | publicSessions |
P1079
|
FINISHED |
| Object | sessions generally open to public and media |
—
|
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: sessions generally open to public and media | Statement: [Parliament of Pakistan, publicSessions, sessions generally open to public and media]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicSessions Context triple: [Parliament of Pakistan, publicSessions, sessions generally open to public and media]
-
A.
sessionType
Indicates the classification or category of a particular session based on its purpose, format, or context.
-
B.
convenesRegularSession
Indicates that an entity formally brings together a group or body for its routine or scheduled meeting.
-
C.
publicAccess
chosen
Indicates that something is available for use, entry, or viewing by the general public without special restrictions or permissions.
-
D.
sessionCount
Indicates the number of distinct sessions associated with an entity or interaction context.
-
E.
parallelConference
Indicates that two or more conferences occur at the same time or overlap in schedule, running in parallel to each other.
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25d8e809881908a58c9a4e3ba07c3 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b6e07748190834022a65ba6d803 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.