Triple
T6186020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schwerin |
E138060
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Odessa |
E38290
|
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: Odessa | Statement: [Schwerin, hasTwinTown, Odessa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Odessa Context triple: [Schwerin, hasTwinTown, Odessa]
-
A.
Odessa
Odessa is a mid-sized city in western Texas known for its oil industry, high school football culture, and role in the Permian Basin energy region.
-
B.
Odessa
Odessa is a central, devoutly religious housekeeper in James Baldwin’s play "The Amen Corner," known for her loyalty and moral grounding amid the story’s family and church conflicts.
-
C.
Odesa
chosen
Odesa is a major port city on the Black Sea in southern Ukraine, known for its historic architecture, multicultural heritage, and key economic and cultural role in the country.
-
D.
Kherson
Kherson is a port city in southern Ukraine near the Black Sea, historically significant as a shipbuilding and industrial center and strategically important due to its location on the Dnieper River.
-
E.
Kryvyi Rih
Kryvyi Rih is a major industrial city in central Ukraine known for its extensive iron ore mining and steel production.
- 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_69c008a8fd408190b7ec6e42934974a6 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062150fc48190877240abe6b6c636 |
completed | March 22, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20d7fbbcc8190902e8f104d9991de |
completed | March 24, 2026, 4:05 a.m. |
Created at: March 22, 2026, 4:19 p.m.