Triple
T35962387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Baptiste |
E1040034
|
entity |
| Predicate | hasReligiousTitleConnotation |
P207114
|
FINISHED |
| Object | forerunner of Christ |
—
|
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: forerunner of Christ | Statement: [Jean Baptiste, hasReligiousTitleConnotation, forerunner of Christ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousTitleConnotation Context triple: [Jean Baptiste, hasReligiousTitleConnotation, forerunner of Christ]
-
A.
religiousTitle
Indicates that one entity holds or is referred to by a specific religious rank, honorific, or clerical title in relation to another entity.
-
B.
hasReligiousAffiliationInName
Indicates that an entity’s name explicitly includes or reflects a religious affiliation or association.
-
C.
hasReligiousName
Indicates that an entity possesses a name specifically associated with a religious context, role, or tradition.
-
D.
hasReligiousCharacter
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
-
E.
hasReligiousType
Indicates that an entity is associated with or classified under a particular religion or religious category.
- 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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:07 p.m.