Triple
T13416717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abu Nuwas |
E313233
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | al-Hasan |
E885098
|
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-Hasan | Statement: [Abu Nuwas, givenName, al-Hasan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: al-Hasan Context triple: [Abu Nuwas, givenName, al-Hasan]
-
A.
Hisham
Hisham is a masculine given name of Arabic origin commonly used across the Muslim world.
-
B.
Abu al-Husayn
Abu al-Husayn is the honorific kunya of the renowned 9th-century Muslim scholar and hadith compiler Imam Muslim ibn al-Hajjaj, author of Sahih Muslim, one of Sunni Islam’s most authoritative hadith collections.
-
C.
Abū al-Ḥasan
chosen
Abū al-Ḥasan is the honorific kunya of the renowned early Arabic grammarian and Qurʾān reciter Al-Kisāʾī, a leading figure of the Kufan school of grammar.
-
D.
Al-Hamza
Al-Hamza is a city in Iraq that serves as one of the principal urban centers of Qadisiyyah Governorate.
-
E.
Hammad
Hammad is a character in the novel "Falling Man," which explores the aftermath of the September 11 attacks.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb6e904819098cc9153fd2feaf5 |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7308095548190afb659b84f2775f2 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:39 p.m.