Triple
T27717559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | hadith of Aisha |
E698862
|
entity |
| Predicate | hasNarratorSchoolRole |
P121011
|
FINISHED |
| Object | teacher of companions |
—
|
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: teacher of companions | Statement: [hadith of Aisha, hasNarratorSchoolRole, teacher of companions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNarratorSchoolRole Context triple: [hadith of Aisha, hasNarratorSchoolRole, teacher of companions]
-
A.
hasEducationalRole
Indicates that an entity holds a specific function, position, or responsibility within an educational context or setting.
-
B.
hasFictionalSchool
Indicates that an entity is associated with or contains a school that exists only within a fictional or imaginary context.
-
C.
schoolRole
chosen
Indicates the specific function, position, or capacity an entity holds within a school context (e.g., student, teacher, administrator).
-
D.
hasFormerPupilRole
Indicates that an entity previously held the role or position of a pupil or student in relation to another entity.
-
E.
hasTeachingRole
Indicates that one entity holds a position or responsibility involving teaching or instruction in relation to another entity.
- F. None of above.
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_69ef591012dc8190a6f1ec994f9f7ff7 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: April 27, 2026, 3:05 p.m.