Triple
T24747367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abd al-Rahman ibn Abi Bakr |
E619037
|
entity |
| Predicate | relationTypeToProphet |
P10690
|
FINISHED |
| Object | Companion |
—
|
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: Companion | Statement: [Abd al-Rahman ibn Abi Bakr, relationTypeToProphet, Companion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationTypeToProphet Context triple: [Abd al-Rahman ibn Abi Bakr, relationTypeToProphet, Companion]
-
A.
linkedToProphet
Indicates a relationship in which an entity is associated or connected in some meaningful way to a prophet.
-
B.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
C.
subjectRelation
Indicates that one entity stands in a specified relational role or connection to another entity.
-
D.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
-
E.
plotRelation
Indicates a narrative connection between two story elements, such as events, characters, or subplots, showing how one influences or relates to the other within the overall plot.
- 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_69e2fabb349881908a13a212a0221a63 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 4:23 a.m.