Triple
T34781092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snake (poem) |
E1002662
|
entity |
| Predicate | containsBiblicalAllusion |
P4481
|
FINISHED |
| Object | Edenic serpent |
—
|
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: Edenic serpent | Statement: [Snake (poem), containsBiblicalAllusion, Edenic serpent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsBiblicalAllusion Context triple: [Snake (poem), containsBiblicalAllusion, Edenic serpent]
-
A.
containsAllusion
Indicates that one entity includes or incorporates an indirect reference or allusion to another entity.
-
B.
scripturalAllusion
chosen
Indicates that one entity references, echoes, or draws upon content, themes, or language from a scriptural or sacred text in relation to another entity.
-
C.
scriptureAllusion
Indicates that one entity makes reference to, echoes, or is inspired by a passage, theme, or element from a scriptural text found in another entity.
-
D.
hasBiblicalConnection
Indicates a relationship in which one entity is connected to another through references, themes, origins, or influences derived from the Bible.
-
E.
hasAllegoricalDepictionsBy
Indicates that one entity is represented through allegorical depictions created by another entity.
- 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a0087de41c48190b2743a26b6d65409 |
completed | May 10, 2026, 1:27 p.m. |
| PD | Predicate disambiguation | batch_6a00870a8bc48190be1385579b8cc1dd |
completed | May 10, 2026, 1:24 p.m. |
Created at: May 3, 2026, 3:59 p.m.