Triple
T11172295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro |
E264303
|
entity |
| Predicate | notableWorkOf |
P4
|
FINISHED |
| Object | Anton Megerdichev |
E1175723
|
NE 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: Anton Megerdichev | Statement: [Metro, notableWorkOf, Anton Megerdichev]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anton Megerdichev Context triple: [Metro, notableWorkOf, Anton Megerdichev]
-
A.
Anton Megerdichev
chosen
Anton Megerdichev is a Russian film director known for his work on action and thriller movies, including the disaster film "Metro."
-
B.
Serguei Mourachov
Serguei Mourachov is a technology entrepreneur best known for co-founding the workplace communication platform Slack.
-
C.
Georgy Tovstonogov
Georgy Tovstonogov was a prominent Soviet and Russian theatre director, best known for leading the Bolshoi Drama Theater in Leningrad and shaping 20th-century Russian stage art.
-
D.
Nikolay Raevsky
Nikolay Raevsky was a prominent Russian general of the Napoleonic Wars, renowned for his leadership and bravery in major battles against Napoleon’s forces.
-
E.
Pyotr Shirshov
Pyotr Shirshov was a Soviet oceanographer, polar explorer, and academician known for his significant contributions to Arctic research and marine science.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e89660208190b1d9e91529f5d246 |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb02b55f4819098f2b18fcf17ef0e |
completed | May 9, 2026, 10:07 p.m. |
Created at: April 8, 2026, 9:29 p.m.