Triple
T16048024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Böblingen |
E389273
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Salo |
E116439
|
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: Salo | Statement: [Böblingen, twinTown, Salo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salo Context triple: [Böblingen, twinTown, Salo]
-
A.
Salo
chosen
Salo is a town in southwestern Finland known for its electronics industry history and location along the Salo River.
-
B.
Tönisvorst
Tönisvorst is a small town in North Rhine-Westphalia, western Germany, known for its agricultural surroundings and proximity to the city of Krefeld.
-
C.
Salzkotten
Salzkotten is a town in North Rhine-Westphalia, Germany, known for its historical salt production and well-preserved medieval center.
-
D.
Sarma
Sarma is a traditional dish of vine or cabbage leaves wrapped around a savory filling, commonly enjoyed throughout Turkish and other Balkan and Middle Eastern cuisines.
-
E.
Lokma
Lokma is a traditional Turkish dessert consisting of small deep-fried dough balls soaked in syrup, often served at celebrations and communal events.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e18360464881909fd4d3bcb4ffb7f5 |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbddc25481908fca660c4f14eaff |
completed | May 10, 2026, 1:14 a.m. |
Created at: April 10, 2026, 4:56 a.m.