Triple
T28626913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emar |
E724548
|
entity |
| Predicate | religiousTextsImportantFor |
P193532
|
FINISHED |
| Object | study of West Semitic ritual |
—
|
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: study of West Semitic ritual | Statement: [Emar, religiousTextsImportantFor, study of West Semitic ritual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousTextsImportantFor Context triple: [Emar, religiousTextsImportantFor, study of West Semitic ritual]
-
A.
religiousTextsUsed
Indicates that certain religious texts are employed or referenced in the practice, teaching, or observance associated with an entity.
-
B.
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).
-
C.
religiousTextMentionedIn
Indicates that a religious text is referenced, cited, or discussed within another work or source.
-
D.
religiousTextTradition
Indicates that a religious text is associated with, originates from, or is authoritative within a particular religious tradition or denomination.
-
E.
religiousTextTranslated
Indicates that a religious text has been translated from one language into another.
- 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_69f01d822ac08190932de59ec2268ed2 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fd49f6dbac81909744373a357b7982 |
completed | May 8, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69fd48ed68f481908374183c66a6b055 |
completed | May 8, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69fd49f612a4819096fe7d5a3bb439ba |
completed | May 8, 2026, 2:27 a.m. |
Created at: April 28, 2026, 4:36 a.m.