Triple
T25857621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark of Toledo |
E651391
|
entity |
| Predicate | religiousTextTranslated |
P174657
|
FINISHED |
| Object | Qur’an |
—
|
NE NERFINISHED |
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: Qur’an | Statement: [Mark of Toledo, religiousTextTranslated, Qur’an]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousTextTranslated Context triple: [Mark of Toledo, religiousTextTranslated, Qur’an]
-
A.
religiousTextOf
Indicates that one entity is a religious text that is sacred to, foundational for, or primarily associated with another entity (such as a religion, denomination, or faith community).
-
B.
religiousTextType
Indicates that one entity is a religious text and specifies the type or category of that religious text in relation to the other entity.
-
C.
religiousTextLanguageOf
Indicates that a particular language is the language in which a given religious text is written or primarily expressed.
-
D.
religiousTextAssociation
Indicates an association where one entity is a religious text that is used by, foundational to, or authoritative for another entity (such as a person, group, or religion).
-
E.
religiousTextCategory
Indicates that a religious text belongs to or is classified under a particular category or type.
- F. None of above. chosen
Provenance (4 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_69e7ab39035c8190be15c8aaee1bb858 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6c5b7e46081909975b05f7298cc0e |
completed | May 3, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c49069e48190a3486b6254a6645b |
completed | May 3, 2026, 3:44 a.m. |
Created at: April 22, 2026, 8:01 a.m.