Triple
T25606492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umm Ayman Barakah |
E641926
|
entity |
| Predicate | caredForDuring |
P28603
|
FINISHED |
| Object | childhood of Prophet Muhammad |
—
|
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: childhood of Prophet Muhammad | Statement: [Umm Ayman Barakah, caredForDuring, childhood of Prophet Muhammad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caredForDuring Context triple: [Umm Ayman Barakah, caredForDuring, childhood of Prophet Muhammad]
-
A.
tookCareOf
chosen
Indicates that one entity provided care, support, or maintenance for another entity over a period of time.
-
B.
ownedDuring
Indicates that one entity possessed or held ownership of another entity for some or all of a specified time interval.
-
C.
occurredDuring
Indicates that one event or action took place within the temporal span of another event or time period.
-
D.
maintainedDuring
Indicates that a certain condition, state, or relationship continues to hold throughout the duration of a specified event or time interval.
-
E.
usedDuring
Indicates that one entity is employed, applied, or active in the course of another entity’s process, event, or time period.
- 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_69e75dc6ccf081908d49578fd36a76d5 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f9e00c9c81909d2372a9ebc8a51f |
completed | May 2, 2026, 1:19 p.m. |
| PD | Predicate disambiguation | batch_69f480789be08190ab252a6de3797200 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 4:38 p.m.