Triple
T14024935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | INS Vikramaditya |
E337432
|
entity |
| Predicate | previousName |
P65
|
FINISHED |
| Object | Baku |
E81696
|
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: Baku | Statement: [INS Vikramaditya, previousName, Baku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baku Context triple: [INS Vikramaditya, previousName, Baku]
-
A.
Baku
chosen
Baku is the capital and largest city of Azerbaijan, known for its rich blend of Islamic heritage and modern architecture on the shores of the Caspian Sea.
-
B.
Kizlyar
Kizlyar is a town in the Republic of Dagestan, Russia, known historically as a frontier settlement and trading center in the North Caucasus region.
-
C.
Akçaabat
Akçaabat is a coastal town and district in Turkey’s Trabzon Province on the Black Sea, known for its historic architecture and distinctive local cuisine.
-
D.
Ashgabat
Ashgabat is the largest city and political, economic, and cultural center of Turkmenistan, known for its grand marble architecture and monumental cityscape.
-
E.
Batumi
Batumi is a major Black Sea resort city in southwestern Georgia known for its beaches, modern skyline, and role as a regional economic and cultural hub.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fa6ca7481908976ce748a1957b1 |
completed | April 14, 2026, 12:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc33170ec8190b0ffe41a567a590b |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:20 p.m.