Triple
T10691175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assyrian religion |
E252010
|
entity |
| Predicate | hasTextualCorpus |
P95315
|
FINISHED |
| Object | ritual texts |
—
|
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: ritual texts | Statement: [Assyrian religion, hasTextualCorpus, ritual texts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTextualCorpus Context triple: [Assyrian religion, hasTextualCorpus, ritual texts]
-
A.
hasNotableCorpus
Indicates that an entity possesses a significant, well-recognized body of work, texts, or collected materials associated with it.
-
B.
hasPartOfCorpus
Indicates that one entity constitutes a component or segment of the overall corpus associated with another entity.
-
C.
hasLimitedCorpus
Indicates that the associated entity possesses only a small or restricted set of available data, texts, or examples for use or analysis.
-
D.
hasTextualBase
Indicates that one entity serves as the underlying textual source or foundation upon which another entity is based or derived.
-
E.
hasCorpusType
Indicates the type or category of corpus associated with an entity (e.g., text, speech, multimodal).
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd3705788190bcbdef93b4c5f574 |
completed | April 9, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69d6dd8cc0788190b4c02a772e4b58b3 |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df47899481909ac0e518d94883cb |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 9:11 p.m.