Triple
T2636253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Al-Muddaththir |
E59752
|
entity |
| Predicate | containsRhetoricalQuestion |
P38652
|
FINISHED |
| Object | What has landed you in Saqar? |
—
|
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: What has landed you in Saqar? | Statement: [Surah Al-Muddaththir, containsRhetoricalQuestion, What has landed you in Saqar?]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsRhetoricalQuestion Context triple: [Surah Al-Muddaththir, containsRhetoricalQuestion, What has landed you in Saqar?]
-
A.
hasKeyQuestion
Indicates that one entity possesses or is associated with a primary or central question relevant to another entity.
-
B.
raisesQuestion
Indicates that one entity causes or prompts a question or doubt to arise about another entity or topic.
-
C.
questionText
chosen
Indicates the textual content of a question as it is posed or displayed.
-
D.
centralQuestion
Indicates that something is the main issue, problem, or inquiry around which a discussion, work, or investigation is focused.
-
E.
canAnswerQuestions
Indicates that an entity has the ability or capacity to respond correctly or appropriately to questions.
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8e1fffc81908e4921690098c8db |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd812849881908f956845a80e0205 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.