Triple
T3304843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishop of Salisbury |
E69421
|
entity |
| Predicate | isHistoricOffice |
P47924
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Bishop of Salisbury, isHistoricOffice, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isHistoricOffice Context triple: [Bishop of Salisbury, isHistoricOffice, true]
-
A.
isHistoric
Indicates that something has significant importance or relevance in history, often due to its age, impact, or role in past events.
-
B.
hasHistoricalRoleAs
Indicates that an entity has served in a specific historical capacity, function, or position during a particular period or context.
-
C.
isHonorificOffice
Indicates that a given office or position is honorary in nature, typically carrying prestige or ceremonial status rather than substantive powers or duties.
-
D.
hasHeldOfficeType
Indicates that an entity has at some time occupied or served in a specified type or category of office or position.
-
E.
historicalStatusOf
Indicates the historical condition, role, or classification that an entity held during a specific past period or context.
- 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_69ad859f218081909458d2cebbf57565 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0c8179081908a2595d1fdb7560a |
completed | March 8, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69ada42625308190be257f16a623a410 |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada526764881908e4bd52938d5374d |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:11 p.m.