Triple
T9939049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Menton |
E194030
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object | Sochi |
E33306
|
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: Sochi | Statement: [Menton, twinnedWith, Sochi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sochi Context triple: [Menton, twinnedWith, Sochi]
-
A.
Sochi
chosen
Sochi is a Russian resort city on the Black Sea coast, known for its subtropical climate, beaches, and as the host of the 2014 Winter Olympics.
-
B.
Krasnaya Polyana
Krasnaya Polyana is a mountain resort settlement in Russia’s Western Caucasus, best known as a major ski and outdoor recreation destination that hosted events during the 2014 Sochi Winter Olympics.
-
C.
Ekaterinodar
Ekaterinodar, now known as Krasnodar, was a major city in southern Russia that served as an important political and military center in the Kuban region.
-
D.
Sochi seaport
Sochi seaport is a prominent Black Sea maritime hub in the Russian resort city of Sochi, known for its passenger terminals, yacht marina, and distinctive Stalinist-era architecture.
-
E.
Luts’k
Luts’k is a historic city in northwestern Ukraine, known as the administrative center of Volyn Oblast and for its well-preserved medieval castle.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e819e08190967b799fd236749e |
completed | April 2, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d228fdb8e48190808702d48470395a |
completed | April 5, 2026, 9:18 a.m. |
Created at: March 30, 2026, 8:44 p.m.