Triple
T10204778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muʿtazilite theology |
E242165
|
entity |
| Predicate | textualSourcesInclude |
P71759
|
FINISHED |
| Object | works of al-Qāḍī ʿAbd al-Jabbār |
—
|
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: works of al-Qāḍī ʿAbd al-Jabbār | Statement: [Muʿtazilite theology, textualSourcesInclude, works of al-Qāḍī ʿAbd al-Jabbār]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textualSourcesInclude Context triple: [Muʿtazilite theology, textualSourcesInclude, works of al-Qāḍī ʿAbd al-Jabbār]
-
A.
textsIncludedIn
Indicates that certain texts are contained within, or form a subset of, a larger collection or body of texts.
-
B.
sourcesInclude
chosen
Indicates that one entity’s content, data, or information is derived from, references, or incorporates material from another specified source.
-
C.
literarySource
Indicates that one entity serves as the written or literary origin, reference, or basis for another entity.
-
D.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
E.
typicalSourceText
Indicates that the related entity is a common or representative textual source from which information, examples, or data about another entity are typically drawn.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa22071c819095febd18dd607978 |
completed | April 6, 2026, 12:42 p.m. |
| PD | Predicate disambiguation | batch_69d39559e5ac8190b88eca75956b7e6a |
completed | April 6, 2026, 11:13 a.m. |
Created at: April 6, 2026, 10:29 a.m.