Triple
T13583012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | سورة الطارق |
E324469
|
entity |
| Predicate | نزلت_بعد |
P104872
|
FINISHED |
| Object | سورة البلد |
—
|
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: سورة البلد | Statement: [سورة الطارق, نزلت_بعد, سورة البلد]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: نزلت_بعد Context triple: [سورة الطارق, نزلت_بعد, سورة البلد]
-
A.
نزلت في
Indicates that an entity arrived at, stayed in, or lodged at a particular place.
-
B.
downfall
Indicates the process or event by which an entity experiences a significant decline, ruin, or loss of power, status, or success.
-
C.
fell
Indicates that an entity moved downward from a higher position to a lower one, typically due to gravity, often unintentionally or uncontrollably.
-
D.
fellOn
Indicates that one entity moved downward, typically due to gravity, and came to rest on the surface of another entity.
-
E.
من حيث النزول
chosen
Indicates the relationship of a text to its place or context of revelation or descent (e.g., where or in what circumstances it was revealed).
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb031e8048190a5f2ea934308036c |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.