Triple
T10113413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badíʻ calendar |
E218296
|
entity |
| Predicate | hasMonthName |
P92265
|
FINISHED |
| Object | Asmáʼ |
E757412
|
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: Asmáʼ | Statement: [Badíʻ calendar, hasMonthName, Asmáʼ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asmáʼ Context triple: [Badíʻ calendar, hasMonthName, Asmáʼ]
-
A.
Asma ul Husna
Asma ul Husna refers to the 99 beautiful names of Allah in Islamic tradition, each expressing a distinct divine attribute.
-
B.
Asmaa
chosen
Asmaa is a feminine given name of Arabic origin commonly used in many Muslim-majority countries.
-
C.
Amna
Amna is a central female character in the Egyptian film "The Nightingale's Prayer," whose tragic story explores themes of honor, revenge, and social oppression.
-
D.
Hafsa
Hafsa is a feminine given name of Arabic origin, historically borne by notable Ottoman royal figures such as Ayşe Hafsa Sultan.
-
E.
Al-Asmaʿi
Al-Asmaʿi was a renowned 8th–9th century Arab philologist, grammarian, and scholar of Bedouin Arabic and poetry, associated with the early development of Arabic linguistic sciences.
- 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd15ed28081909a812e0634799ef8 |
completed | April 2, 2026, 2:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cc20ff4481909cdd916e92eda2f6 |
completed | April 5, 2026, 8:54 p.m. |
Created at: March 30, 2026, 9:04 p.m.