Triple
T27717590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | hadith of Aisha |
E698862
|
entity |
| Predicate | hasNotableReportAbout |
P18677
|
FINISHED |
| Object | incident of ifk |
—
|
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: incident of ifk | Statement: [hadith of Aisha, hasNotableReportAbout, incident of ifk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableReportAbout Context triple: [hadith of Aisha, hasNotableReportAbout, incident of ifk]
-
A.
hasNotableIssue
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
B.
hasNotableResponse
Indicates that an entity has received a significant, noteworthy, or widely recognized reaction or feedback in response to it.
-
C.
hasNotableIncident
chosen
Indicates that an entity is associated with a significant or noteworthy event, occurrence, or incident.
-
D.
notableReport
Indicates that an entity has produced, authored, or is otherwise associated with a report that is considered notable or significant.
-
E.
hasNotabilityNote
Indicates that there is an associated note or annotation explaining the significance, prominence, or special relevance of the subject.
- 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_69feba0f09508190b3e871c62b19ec7f |
completed | May 9, 2026, 4:37 a.m. |
| PD | Predicate disambiguation | batch_69feb957fe7c8190969fb31a6d1a59c8 |
completed | May 9, 2026, 4:34 a.m. |
Created at: April 27, 2026, 3:05 p.m.