Triple
T17265715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Обь |
E419121
|
entity |
| Predicate | впадаетВ |
P22011
|
FINISHED |
| Object |
Обская губа
Обская губа — крупный залив Карского моря на севере Западной Сибири, образующий эстуарий реки Обь и являющийся важным природным и транспортным регионом Арктики России.
|
E1259991
|
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: Обская губа | Statement: [Обь, впадаетВ, Обская губа]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Обская губа Context triple: [Обь, впадаетВ, Обская губа]
-
A.
Begovaya
Begovaya is a metro station in Saint Petersburg, Russia, serving as a modern terminal stop on one of the city’s metro lines.
-
B.
Novorybnaya
Novorybnaya is a small rural settlement located along the Khatanga River in the remote Arctic region of northern Siberia, Russia.
-
C.
Kholmogory
Kholmogory is a historic Russian town in the Arkhangelsk region that served as an important early northern trading and administrative center.
-
D.
Urzhum
Urzhum is a small historic town in Kirov Oblast, Russia, known as the birthplace of prominent Soviet leader Sergei Kirov.
-
E.
Malyovitsa
Malyovitsa is a prominent peak in Bulgaria renowned for its rugged alpine scenery and popularity among climbers and hikers.
- 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: Обская губа Triple: [Обь, впадаетВ, Обская губа]
Generated description
Обская губа — крупный залив Карского моря на севере Западной Сибири, образующий эстуарий реки Обь и являющийся важным природным и транспортным регионом Арктики России.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Обская губа Target entity description: Обская губа — крупный залив Карского моря на севере Западной Сибири, образующий эстуарий реки Обь и являющийся важным природным и транспортным регионом Арктики России.
-
A.
Begovaya
Begovaya is a metro station in Saint Petersburg, Russia, serving as a modern terminal stop on one of the city’s metro lines.
-
B.
Novorybnaya
Novorybnaya is a small rural settlement located along the Khatanga River in the remote Arctic region of northern Siberia, Russia.
-
C.
Kholmogory
Kholmogory is a historic Russian town in the Arkhangelsk region that served as an important early northern trading and administrative center.
-
D.
Urzhum
Urzhum is a small historic town in Kirov Oblast, Russia, known as the birthplace of prominent Soviet leader Sergei Kirov.
-
E.
Malyovitsa
Malyovitsa is a prominent peak in Bulgaria renowned for its rugged alpine scenery and popularity among climbers and hikers.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f44ec7c81909a925fc8692b0a6c |
completed | April 19, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01794641648190a5db87ecb359c17a |
completed | May 11, 2026, 6:37 a.m. |
| NEDg | Description generation | batch_6a017abddcc48190872f77b62ac9896e |
completed | May 11, 2026, 6:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a017b7e72908190913215717fb04b0f |
completed | May 11, 2026, 6:47 a.m. |
Created at: April 10, 2026, 5:40 a.m.