Triple
T13356860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ibn Zuhr |
E318714
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Al-Taysir
Al-Taysir is a seminal medical treatise by the Andalusian physician Ibn Zuhr that systematizes clinical observations and treatments in a clear, practical format.
|
E1037578
|
NE FINISHED |
How this triple was built (4 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-Taysir | Statement: [Ibn Zuhr, notableWork, Al-Taysir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Al-Taysir Context triple: [Ibn Zuhr, notableWork, Al-Taysir]
-
A.
Al-Hareeq
Al-Hareeq is a town in central Saudi Arabia known for its agricultural activity, particularly date palm cultivation, within the Riyadh region.
-
B.
Khath‘am
Khath‘am is an ancient Arab tribe known from early Islamic history, to which the companion Asma bint Umais belonged.
-
C.
Taysir
Taysir is an Arabic male given name meaning "facilitation" or "making things easier," commonly used across the Arab world.
-
D.
Al-Muthirah
Al-Muthirah is an alternative name for Bara'ah, a term associated with Islamic concepts of disavowal or separation from wrongdoing and its people.
-
E.
al-Nabigha
al-Nabigha was an Arab woman of pre-Islamic Mecca best known as the mother of the prominent early Islamic military commander and statesman Amr ibn al-As.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Al-Taysir Triple: [Ibn Zuhr, notableWork, Al-Taysir]
Generated description
Al-Taysir is a seminal medical treatise by the Andalusian physician Ibn Zuhr that systematizes clinical observations and treatments in a clear, practical format.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Al-Taysir Target entity description: Al-Taysir is a seminal medical treatise by the Andalusian physician Ibn Zuhr that systematizes clinical observations and treatments in a clear, practical format.
-
A.
Al-Hareeq
Al-Hareeq is a town in central Saudi Arabia known for its agricultural activity, particularly date palm cultivation, within the Riyadh region.
-
B.
Khath‘am
Khath‘am is an ancient Arab tribe known from early Islamic history, to which the companion Asma bint Umais belonged.
-
C.
Taysir
Taysir is an Arabic male given name meaning "facilitation" or "making things easier," commonly used across the Arab world.
-
D.
Al-Muthirah
Al-Muthirah is an alternative name for Bara'ah, a term associated with Islamic concepts of disavowal or separation from wrongdoing and its people.
-
E.
al-Nabigha
al-Nabigha was an Arab woman of pre-Islamic Mecca best known as the mother of the prominent early Islamic military commander and statesman Amr ibn al-As.
- F. None of above. chosen
Provenance (5 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcd4cb008190af99c4856e76ac08 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f72677b2a48190aad30f3ee6cacefb |
completed | May 3, 2026, 10:41 a.m. |
| NEDg | Description generation | batch_69f727512c94819091985c7942f40b31 |
completed | May 3, 2026, 10:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f72b77d650819092c02f6488b2cfb2 |
completed | May 3, 2026, 11:03 a.m. |
Created at: April 9, 2026, 9:32 p.m.