Triple
T6590142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greifswald |
E159331
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Pomerode |
E278156
|
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: Pomerode | Statement: [Greifswald, twinTown, Pomerode]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pomerode Context triple: [Greifswald, twinTown, Pomerode]
-
A.
Pomerode
chosen
Pomerode is a small city in southern Brazil renowned for its strong German heritage, architecture, and cultural traditions.
-
B.
São Rafael
São Rafael was one of the ships in Vasco da Gama’s pioneering First Portuguese India Armada that opened the sea route from Europe to India.
-
C.
Panguipulli
Panguipulli is a scenic town in southern Chile known for its lakeside setting, surrounding volcanoes, and role as a gateway to the Andean lake district.
-
D.
Neiva
Neiva is a major city in southwestern Colombia known as the economic and cultural center of the upper Magdalena River valley.
-
E.
Trelew
Trelew is a city in the Chubut Province of Argentine Patagonia, known as a commercial and transportation hub with strong Welsh cultural heritage.
- 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_69c688366ce8819083f8883983c0df92 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6aeb201e88190808cf5779349f96c |
completed | March 27, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d57bde388190919ff6820e1b9610 |
completed | March 27, 2026, 7:07 p.m. |
Created at: March 27, 2026, 1:55 p.m.