Triple
T1353132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hafsa bint Umar |
E28926
|
entity |
| Predicate | hadithStatus |
P27934
|
FINISHED |
| Object | narrator of hadith |
—
|
LITERAL 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: narrator of hadith | Statement: [Hafsa bint Umar, hadithStatus, narrator of hadith]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadithStatus Context triple: [Hafsa bint Umar, hadithStatus, narrator of hadith]
-
A.
quranicStatus
Indicates the status or classification of something in relation to its recognition, treatment, or role within the Quran.
-
B.
halakhicStatus
Indicates the formal standing or classification of an entity according to Jewish law (halakha), especially in terms of what is religiously permitted, required, or prohibited.
-
C.
status
Indicates the current condition, state, or standing of an entity within a given context.
-
D.
statusInIran
Indicates the legal, social, or political standing or condition of an entity specifically within the context of Iran.
-
E.
deciphermentStatus
Indicates the degree to which something (such as a text, code, or inscription) has been successfully decoded or interpreted.
- F. None of above. chosen
Provenance (4 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_69a498571d248190a0ac9eb02d97097f |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c26d0c4481908fddda89242a57b3 |
completed | March 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69a4bef7700c819099b294e8d9320e70 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c20fd1fc8190977a768b1ed2d23b |
completed | March 1, 2026, 10:47 p.m. |
Created at: March 1, 2026, 7:56 p.m.