Triple
T34375267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark 16:1 |
E882268
|
entity |
| Predicate | parallelPassageTopic |
P51251
|
FINISHED |
| Object | women at the tomb |
—
|
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: women at the tomb | Statement: [Mark 16:1, parallelPassageTopic, women at the tomb]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parallelPassageTopic Context triple: [Mark 16:1, parallelPassageTopic, women at the tomb]
-
A.
parallelPassage
chosen
Indicates that one text segment corresponds closely in content or structure to another, such that they can be considered parallel versions or accounts of the same material.
-
B.
structureParallels
Indicates that the structural organization or arrangement of one entity closely corresponds to or mirrors that of another.
-
C.
parallel
Indicates that two or more entities maintain a constant separation and direction without intersecting or converging.
-
D.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
E.
passage
Indicates that an entity moves through, across, or past another entity or spatial region.
- 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_69f349bf5d7481908dd5da4cbdf74047 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 1:59 a.m.