Triple
T687386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow Oblast |
E13313
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Lyubertsy
Lyubertsy is a city in Russia that serves as a major suburban and industrial center just southeast of Moscow.
|
E126824
|
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: Lyubertsy | Statement: [Moscow Oblast, contains, Lyubertsy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lyubertsy Context triple: [Moscow Oblast, contains, Lyubertsy]
-
A.
Elektrostal
Elektrostal is an industrial city in Russia known for its metallurgical and engineering industries, located east of Moscow.
-
B.
Sergiyev Posad
Sergiyev Posad is a historic Russian town best known as a major center of Orthodox Christianity and home to the UNESCO-listed Trinity Lavra of St. Sergius monastery.
-
C.
Dmitrov
Dmitrov is a historic town in Moscow Oblast, Russia, located north of Moscow and known for its medieval kremlin and role as a regional cultural center.
-
D.
Podolsk
Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
-
E.
Novo-Ogaryovo
Novo-Ogaryovo is a suburban governmental estate outside Moscow that serves as one of the primary official residences of Russian President Vladimir Putin.
- 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: Lyubertsy Triple: [Moscow Oblast, contains, Lyubertsy]
Generated description
Lyubertsy is a city in Russia that serves as a major suburban and industrial center just southeast of Moscow.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lyubertsy Target entity description: Lyubertsy is a city in Russia that serves as a major suburban and industrial center just southeast of Moscow.
-
A.
Elektrostal
Elektrostal is an industrial city in Russia known for its metallurgical and engineering industries, located east of Moscow.
-
B.
Sergiyev Posad
Sergiyev Posad is a historic Russian town best known as a major center of Orthodox Christianity and home to the UNESCO-listed Trinity Lavra of St. Sergius monastery.
-
C.
Dmitrov
Dmitrov is a historic town in Moscow Oblast, Russia, located north of Moscow and known for its medieval kremlin and role as a regional cultural center.
-
D.
Podolsk
Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
-
E.
Novo-Ogaryovo
Novo-Ogaryovo is a suburban governmental estate outside Moscow that serves as one of the primary official residences of Russian President Vladimir Putin.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0953fb481909e1d4177ee191351 |
completed | March 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4bf512bc81908ff403ce87337a0d |
completed | March 7, 2026, 4:01 p.m. |
| NEDg | Description generation | batch_69ac4f7da1b48190b758c1900ef5bc8f |
completed | March 7, 2026, 4:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac4fd709e88190b7082b7111e24832 |
completed | March 7, 2026, 4:18 p.m. |
Created at: March 1, 2026, 7:36 p.m.