Triple
T4631564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arkhangelsk |
E101428
|
entity |
| Predicate | servedAsMainSeaportUntil |
P57849
|
FINISHED |
| Object | early 18th century |
—
|
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: early 18th century | Statement: [Arkhangelsk, servedAsMainSeaportUntil, early 18th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedAsMainSeaportUntil Context triple: [Arkhangelsk, servedAsMainSeaportUntil, early 18th century]
-
A.
isLargestSeaportOn
Indicates that a seaport is the largest seaport located on a specified geographic feature, such as a coast, island, or body of water.
-
B.
servedAsNationalCapitalUntil
Indicates that a place functioned as the national capital of a country or state up to a specified end date, after which it no longer held that status.
-
C.
isLargestSeaportIn
Indicates that one location is the largest seaport within a specified geographic or political region.
-
D.
isBusiestSeaportIn
Indicates that a seaport handles the highest volume of traffic or activity compared to all other seaports within a specified region or area.
-
E.
isAmongLargestPortsIn
Indicates that a port ranks among the largest ports within a specified geographic or administrative area.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a32d6408190962e60b9bce7560d |
completed | March 20, 2026, 2:31 p.m. |
| PD | Predicate disambiguation | batch_69bd5233cb5081908807e2b150f0ca06 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56f6e75481909c487a94a2c2d0ba |
completed | March 20, 2026, 2:17 p.m. |
Created at: March 20, 2026, 1:13 p.m.