Triple
T4030579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thorney Abbey (translated relics) |
E83698
|
entity |
| Predicate | associatedSaintOccupation |
P53541
|
FINISHED |
| Object | abbot |
—
|
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: abbot | Statement: [Thorney Abbey (translated relics), associatedSaintOccupation, abbot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedSaintOccupation Context triple: [Thorney Abbey (translated relics), associatedSaintOccupation, abbot]
-
A.
typeOfSaint
Indicates that one entity is classified as a specific kind or category of saint in relation to another entity.
-
B.
religiousFigure
Indicates that one entity is recognized or designated as a religious leader, authority, or sacred person in relation to another entity.
-
C.
linkedToSaint
Indicates that one entity has a direct association or connection with a saint.
-
D.
nationalPatronSaint
Indicates that one entity is recognized as the official patron saint of a particular nation.
-
E.
venerationOfSaints
Indicates the act of showing honor, reverence, or devotional respect toward saints.
- 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_69aed92e29ac819080f7a98b594fec05 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaf1d8208190951a20ad7e5ab7bc |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fe440c819093a7fa22c4ff3f1a |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa815f2c8190818c9ffd9d1bf478 |
completed | March 9, 2026, 4:51 p.m. |
Created at: March 9, 2026, 3:36 p.m.