Triple
T4283520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novgorod |
E97210
|
entity |
| Predicate | economicRoleHistorical |
P29914
|
FINISHED |
| Object | trading hub |
—
|
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: trading hub | Statement: [Novgorod, economicRoleHistorical, trading hub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicRoleHistorical Context triple: [Novgorod, economicRoleHistorical, trading hub]
-
A.
notableHistoricalFigureRole
Indicates that an entity is recognized as a historically significant person who played a particular role or held a specific position in history.
-
B.
hasHistoricalRoleAs
chosen
Indicates that an entity has served in a specific historical capacity, function, or position during a particular period or context.
-
C.
ethnicRole
Indicates a role, function, or social position that is specifically associated with or defined by an entity’s ethnicity.
-
D.
notableHolderOccupation
Indicates that a person notably associated with an entity (e.g., an award, office, or title) held a particular occupation or professional role.
-
E.
countryNationalRole
Indicates the official function, position, or responsibility that an entity holds at the national level within a specific country.
- 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3503a84548190989a96d1a30d6ef7 |
completed | March 12, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69b347fc4c0c8190a7fcd814e27308a5 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:07 p.m.