Triple
T8608131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alma-Ata Protocol |
E203854
|
entity |
| Predicate | signedIn |
P441
|
FINISHED |
| Object | Alma-Ata |
E50745
|
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: Alma-Ata | Statement: [Alma-Ata Protocol, signedIn, Alma-Ata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alma-Ata Context triple: [Alma-Ata Protocol, signedIn, Alma-Ata]
-
A.
Alma-Atinskaya
Alma-Atinskaya is a southern terminus station of the Moscow Metro, serving as one endpoint of the Zamoskvoretskaya Line.
-
B.
Karaganda
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
-
C.
Syktyvkar
Syktyvkar is the capital city of the Komi Republic in northwestern Russia, known as an administrative, cultural, and economic center of the region.
-
D.
Almaty
chosen
Almaty is the largest city and main commercial and cultural center of Kazakhstan, located in the country’s mountainous southeast.
-
E.
Yoshkar-Ola
Yoshkar-Ola is a city in central Russia that serves as the administrative, cultural, and economic center of the Mari El Republic.
- 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_69ca832c23e4819095a9f3eea4a21828 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46ec301881908ce148a3f07069fe |
completed | March 31, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea909757c819095dd38644c21af33 |
completed | April 2, 2026, 5:36 p.m. |
Created at: March 30, 2026, 6:25 p.m.