Triple
T36732329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew–Luke–Mark |
E907373
|
entity |
| Predicate | proposesThirdGospel |
P187101
|
FINISHED |
| Object | Gospel of Mark |
—
|
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: Gospel of Mark | Statement: [Matthew–Luke–Mark, proposesThirdGospel, Gospel of Mark]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proposesThirdGospel Context triple: [Matthew–Luke–Mark, proposesThirdGospel, Gospel of Mark]
-
A.
proposesSecondGospel
Indicates that an entity puts forward or advocates for the idea, theory, or existence of a second gospel.
-
B.
proposesFirstGospel
Indicates that an entity puts forward or advocates a particular work as the earliest or original gospel in a given context.
-
C.
positionAmongGospels
Indicates the numerical order or placement of a given gospel within the sequence of all gospels.
-
D.
uniqueToGospel
Indicates that a particular element (such as a story, saying, or detail) appears only in one specific Gospel and not in any of the others.
-
E.
parallelGospel
Indicates that one gospel text corresponds closely to another in content, structure, or narrative, allowing them to be compared side by side as parallel accounts.
- 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_69f76e75aa6881909b844d00a3888ee5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
| PDg | Predicate description generation | batch_69fb3424724c8190ba55ecf66fa0b171 |
completed | May 6, 2026, 12:29 p.m. |
Created at: May 3, 2026, 4:12 p.m.