Triple
T20464732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Episcopus Cicestrensis |
E502016
|
entity |
| Predicate | titleAppliesTo |
P96985
|
FINISHED |
| Object | incumbent Bishop of Chichester |
—
|
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: incumbent Bishop of Chichester | Statement: [Episcopus Cicestrensis, titleAppliesTo, incumbent Bishop of Chichester]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleAppliesTo Context triple: [Episcopus Cicestrensis, titleAppliesTo, incumbent Bishop of Chichester]
-
A.
appliedToTitle
chosen
Indicates that something (such as a rule, action, or attribute) is applied specifically to a given title.
-
B.
titleAffirms
Indicates that a title explicitly asserts, confirms, or supports the truth or validity of a particular claim, idea, or relationship.
-
C.
titleThrough
Indicates a relationship where one entity holds or is identified by a specific title by means of, or via the mediation of, another entity or context.
-
D.
titleImplies
Indicates that holding or being assigned a particular title suggests or entails a certain role, status, or set of responsibilities.
-
E.
nameAppliesTo
Indicates that a particular name is assigned to, or valid for use with, a specific 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_69e0b4ad4940819098cf2ff6413574e5 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a9489081908990c691a36ba04d |
completed | April 20, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:33 a.m.