Triple
T597280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senior Deacon |
E11413
|
entity |
| Predicate | followsOffice |
P134
|
FINISHED |
| Object | Junior Deacon in the progressive line (in many lodges) |
—
|
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: Junior Deacon in the progressive line (in many lodges) | Statement: [Senior Deacon, followsOffice, Junior Deacon in the progressive line (in many lodges)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsOffice Context triple: [Senior Deacon, followsOffice, Junior Deacon in the progressive line (in many lodges)]
-
A.
followsWork
Indicates that one work (such as a publication, version, or creative piece) comes directly after another in sequence or succession.
-
B.
follows
chosen
Indicates that one entity comes after, moves behind, or acts in accordance with another entity in time, space, or sequence.
-
C.
includedOffice
Indicates that one office is contained within, or forms part of, another office or organizational unit.
-
D.
relatesToOffice
Indicates that one entity has a connection, association, or relevance to an office, its functions, or its environment.
-
E.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49dc4f7d08190990f70b9b3af6ce5 |
completed | March 1, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69a49cf59cd0819084e67981cb371e25 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.