Triple
T19057784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irkutsk Time |
E466443
|
entity |
| Predicate | appliesToCity |
P4810
|
FINISHED |
| Object | Chita |
—
|
NE NERFINISHED |
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: Chita | Statement: [Irkutsk Time, appliesToCity, Chita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chita Context triple: [Irkutsk Time, appliesToCity, Chita]
-
A.
Chita
chosen
Chita is a city in southeastern Siberia, Russia, serving as an important administrative, cultural, and transportation center of Zabaykalsky Krai.
-
B.
Chita Peninsula
The Chita Peninsula is a landform in central Japan’s Aichi Prefecture that separates Ise Bay from Mikawa Bay and hosts industrial cities, ports, and coastal communities.
-
C.
Amursk
Amursk is a small industrial town in Russia’s Far East, situated on the Amur River and known for its timber and pulp-and-paper industries.
-
D.
Komsomolsk-on-Amur
Komsomolsk-on-Amur is a major industrial city in Russia’s Khabarovsk Krai, known for its shipbuilding and aircraft manufacturing industries in the Russian Far East.
-
E.
Tobolsk
Tobolsk is a historic Siberian town in Russia known for its Kremlin and as a place of exile and imprisonment during the late imperial period.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc0742288190a594be859184841a |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 10, 2026, 12:03 p.m.