Triple
T1766854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leningrad Oblast |
E38781
|
entity |
| Predicate | hasPort |
P35
|
FINISHED |
| Object |
Ust-Luga
Ust-Luga is a major Russian Baltic Sea port town that serves as a key cargo and energy export hub for the Leningrad Oblast region.
|
E215452
|
NE FINISHED |
How this triple was built (4 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: Ust-Luga | Statement: [Leningrad Oblast, hasPort, Ust-Luga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ust-Luga Context triple: [Leningrad Oblast, hasPort, Ust-Luga]
-
A.
Kholmogory
Kholmogory is a historic Russian town in the Arkhangelsk region that served as an important early northern trading and administrative center.
-
B.
Severodvinsk
Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
-
C.
Shakhovskoye
Shakhovskoye is a rural locality in Russia known primarily as the birthplace of Soviet politician Mikhail Suslov.
-
D.
Pechenga
Pechenga is a region in Russia’s far northwest, near the Barents Sea and the Norwegian border, historically known as Petsamo when it belonged to Finland.
-
E.
Kholmsk
Kholmsk is a port town on the western coast of Sakhalin Island in Russia, serving as an important maritime transport hub in the Sea of Japan.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ust-Luga Triple: [Leningrad Oblast, hasPort, Ust-Luga]
Generated description
Ust-Luga is a major Russian Baltic Sea port town that serves as a key cargo and energy export hub for the Leningrad Oblast region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ust-Luga Target entity description: Ust-Luga is a major Russian Baltic Sea port town that serves as a key cargo and energy export hub for the Leningrad Oblast region.
-
A.
Kholmogory
Kholmogory is a historic Russian town in the Arkhangelsk region that served as an important early northern trading and administrative center.
-
B.
Severodvinsk
Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
-
C.
Shakhovskoye
Shakhovskoye is a rural locality in Russia known primarily as the birthplace of Soviet politician Mikhail Suslov.
-
D.
Pechenga
Pechenga is a region in Russia’s far northwest, near the Barents Sea and the Norwegian border, historically known as Petsamo when it belonged to Finland.
-
E.
Kholmsk
Kholmsk is a port town on the western coast of Sakhalin Island in Russia, serving as an important maritime transport hub in the Sea of Japan.
- F. None of above. chosen
Provenance (5 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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa646914048190bbe282a3d4768835 |
completed | March 6, 2026, 5:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3bc8fe8819085a8adaf9dcd5c1b |
completed | March 8, 2026, 10:10 p.m. |
| NEDg | Description generation | batch_69adf494f0288190bf77285d18fcd3d9 |
completed | March 8, 2026, 10:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adf51f49488190b9b0465b4da685c1 |
completed | March 8, 2026, 10:15 p.m. |
Created at: March 4, 2026, 7:31 p.m.