Triple
T28709751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Epirus Nova |
E729795
|
entity |
| Predicate | hadBishops |
P165246
|
FINISHED |
| Object | Dyrrhachium |
—
|
NE NERFINISHED |
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: Dyrrhachium | Statement: [Epirus Nova, hadBishops, Dyrrhachium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadBishops Context triple: [Epirus Nova, hadBishops, Dyrrhachium]
-
A.
hasPreviousBishop
Indicates that one bishop previously held the same episcopal position or office as another bishop.
-
B.
hasBishop
Indicates that one entity possesses, is assigned, or is associated with a bishop in relation to another entity.
-
C.
hasFirstBishop
Indicates that an entity is associated with a specific bishop who is designated as its first bishop in a sequence or hierarchy.
-
D.
hasNumberOfBishops
Indicates the relationship that specifies how many bishops are associated with a given entity.
-
E.
majorityOfBishopsFrom
Indicates that, within a given group or context, more than half of the bishops originate from or are associated with a specified place or source.
- 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_69f043e7d5a4819094b18aca10b1e024 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 28, 2026, 5:47 a.m.