Triple
T30794678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Cathedral All Saints |
E784194
|
entity |
| Predicate | hasClergyRankSeated |
P3655
|
FINISHED |
| Object | archbishop |
—
|
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: archbishop | Statement: [Metropolitan Cathedral All Saints, hasClergyRankSeated, archbishop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClergyRankSeated Context triple: [Metropolitan Cathedral All Saints, hasClergyRankSeated, archbishop]
-
A.
hasClergyRankOver
Indicates that one clergy member holds a higher ecclesiastical rank or authority than another within a religious hierarchy.
-
B.
hasLiturgicalRank
chosen
Indicates that an entity is assigned a specific status or level within a liturgical or religious ceremonial hierarchy.
-
C.
hasClergy
Indicates that an organization or institution possesses or is served by members of the clergy.
-
D.
hasClergyOrder
Indicates that an entity is associated with, or belongs to, a specific religious or clerical order.
-
E.
hasClergyType
Indicates the specific category or role of clergy associated with an 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_69f224b2e2a48190b19aa43db9da5b67 |
completed | April 29, 2026, 3:33 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. |
Created at: April 29, 2026, 8:42 p.m.