Triple
T4503371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ottoman navy |
E101274
|
entity |
| Predicate | mainBase |
P2909
|
FINISHED |
| Object | Sinop |
E114644
|
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: Sinop | Statement: [Ottoman navy, mainBase, Sinop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sinop Context triple: [Ottoman navy, mainBase, Sinop]
-
A.
Sinop
chosen
Sinop is a historic port city on Turkey’s Black Sea coast, long valued for its strategic harbor and role in regional trade and defense.
-
B.
Dzhankoy
Dzhankoy is a town in northern Crimea that serves as a key regional railway junction and transport hub.
-
C.
Kerch
Kerch is a historic port city in eastern Crimea, strategically located on the Kerch Strait linking the Black Sea and the Sea of Azov.
-
D.
Sevastopolskaya
Sevastopolskaya is a Moscow Metro station serving the Serpukhovsko–Timiryazevskaya Line in the city’s southern part.
-
E.
Komsomolskaya
Komsomolskaya is one of Moscow Metro’s most famous and ornate stations, renowned for its grand Baroque-style decor and elaborate mosaics.
- 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_69bd43d175248190894dc58b5b395c26 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56fca7d4819081deb34628e04f00 |
completed | March 20, 2026, 2:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd6f958de0819082d17c165d25e703 |
completed | March 20, 2026, 4:02 p.m. |
Created at: March 20, 2026, 1:01 p.m.