Triple
T327441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Council of Nicaea |
E6549
|
entity |
| Predicate | numberOfBishopsAttending |
P1131
|
FINISHED |
| Object | about 220 |
—
|
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: about 220 | Statement: [First Council of Nicaea, numberOfBishopsAttending, about 220]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBishopsAttending Context triple: [First Council of Nicaea, numberOfBishopsAttending, about 220]
-
A.
hasBishop
Indicates that one entity possesses, is assigned, or is associated with a bishop in relation to another entity.
-
B.
maximumNumberOfKnightsAndLadies
Indicates the greatest allowable or observed count of entities classified as knights and ladies within a given context or scenario.
-
C.
hasSuffraganBishop
Indicates that one bishop holds the position of suffragan (subordinate or assistant) bishop in relation to another bishop or ecclesiastical authority.
-
D.
numberOfParticipants
chosen
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
E.
hasClergy
Indicates that an organization or institution possesses or is served by members of the clergy.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea98fa2c8190a5b44f4a26543a17 |
completed | Feb. 28, 2026, 1:16 p.m. |
| PD | Predicate disambiguation | batch_69a2e94aab1c8190b8654708c87eeb91 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.