Triple
T10420491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Waqi'ah |
E245633
|
entity |
| Predicate | followedBySurah |
P30312
|
FINISHED |
| Object | Al-Hadid |
E256487
|
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: Al-Hadid | Statement: [Al-Waqi'ah, followedBySurah, Al-Hadid]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Al-Hadid Context triple: [Al-Waqi'ah, followedBySurah, Al-Hadid]
-
A.
Al-Hadid
chosen
Al-Hadid is the 57th chapter (surah) of the Qur’an, known for its emphasis on God’s power, the transient nature of worldly life, and the importance of charity and faith.
-
B.
The Iron
The Iron is the English title of Surah Al-Hadid, the 57th chapter of the Qur’an, which emphasizes faith, charity, and the transient nature of worldly life.
-
C.
The Iron
The Iron is the nickname of Scunthorpe United F.C., an English professional football club traditionally associated with the town’s steel industry.
-
D.
Huwarin
Huwarin is a town in present-day Syria historically noted as the place where the Umayyad caliph Yazid I died.
-
E.
Erfe
Erfe is the surname of Elaine Mendoza Erfe, best known as the wife of American comedian Dave Chappelle.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea2bee2081908e5e65df9100d463 |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fc17c874819096b656056ed2dd8a |
completed | April 9, 2026, 7:20 p.m. |
Created at: April 6, 2026, 12:11 p.m.