Triple
T2016395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Az-Zukhruf |
E44004
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Az Zukhruf |
E225865
|
NE 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: Az Zukhruf | Statement: [Surah Az-Zukhruf, name, Az Zukhruf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Az Zukhruf Context triple: [Surah Az-Zukhruf, name, Az Zukhruf]
-
A.
Az-Zukhruf
chosen
Az-Zukhruf is the 43rd chapter of the Qur’an, known for emphasizing the folly of worldly adornments and the importance of sincere faith in God.
-
B.
As-Sab‘ al-Mathani
As-Sab‘ al-Mathani is an honorific title for Surah Al-Fatiha, highlighting its special status as a frequently recited, foundational chapter of the Qur’an.
-
C.
Badhl al-Majhud
Badhl al-Majhud is a renowned multi-volume scholarly commentary on the hadith collection Sunan Abu Dawud, widely used in advanced Islamic studies.
-
D.
Lisān al-Ghayb
Lisān al-Ghayb is the honorific epithet of the Persian poet Hafez, highlighting his perceived mystical insight into the unseen and the divine.
-
E.
Al Muntaha
Al Muntaha is a fine-dining restaurant located near the top of Dubai’s iconic Burj Al Arab, known for its upscale cuisine and panoramic views of the city and Persian Gulf.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8ccdb7c81909f6b3c96f79fcdfc |
completed | March 7, 2026, 5:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1fe5ad548190b4a64c5320b99c6d |
completed | March 9, 2026, 1:18 a.m. |
Created at: March 4, 2026, 7:38 p.m.