Triple
T341061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qiyas |
E6837
|
entity |
| Predicate | hasDebateOn |
P8604
|
FINISHED |
| Object | extent of its authority |
—
|
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: extent of its authority | Statement: [Qiyas, hasDebateOn, extent of its authority]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDebateOn Context triple: [Qiyas, hasDebateOn, extent of its authority]
-
A.
hasDebate
chosen
Indicates that there is a formal discussion or argument between entities, typically presenting opposing viewpoints on a topic.
-
B.
debatedAt
Indicates that a debate or formal discussion involving the subject took place at the specified location or event.
-
C.
debateCountGeneralElection
Indicates the number of debates held in the context of a general election.
-
D.
languageOfDebate
Indicates that a specified language is the one used for conducting a particular debate.
-
E.
wasContestedIn
Indicates that an event, position, or decision was the subject of competition, dispute, or challenge within a particular context or proceeding.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eae611f88190955fbebe2b01835b |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e95197fc8190820e8ebd0d7d27fa |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.