Triple
T2870004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Al-Inshiqaq |
E63535
|
entity |
| Predicate | containsRhetoricalQuestions |
P43427
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Surah Al-Inshiqaq, containsRhetoricalQuestions, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsRhetoricalQuestions Context triple: [Surah Al-Inshiqaq, containsRhetoricalQuestions, true]
-
A.
hasKeyQuestion
Indicates that one entity possesses or is associated with a primary or central question relevant to another entity.
-
B.
hasOpenQuestions
Indicates that there are unresolved or unanswered issues, problems, or inquiries associated with the referenced entity or context.
-
C.
canAnswerQuestions
Indicates that an entity has the ability or capacity to respond correctly or appropriately to questions.
-
D.
raisesQuestion
Indicates that one entity causes or prompts a question or doubt to arise about another entity or topic.
-
E.
questionText
Indicates the textual content of a question as it is posed or displayed.
- 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_69ab4c42fb8c8190b36e161d47c03b81 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfe15ff081908dd1dad62c292b2b |
completed | March 7, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69abdd142e4c8190b424cb0c5ff40d04 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abde2cdcc48190827195d3ae70aa19 |
completed | March 7, 2026, 8:13 a.m. |
Created at: March 6, 2026, 10:02 p.m.