Triple
T17773393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FC Thun |
E443697
|
entity |
| Predicate | hasRivalryWith |
P893
|
FINISHED |
| Object |
FC Bern
FC Bern is a Swiss football club based in the city of Bern, historically competing in the national league system and known for its local rivalries.
|
E1286496
|
NE FINISHED |
How this triple was built (4 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: FC Bern | Statement: [FC Thun, hasRivalryWith, FC Bern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FC Bern Context triple: [FC Thun, hasRivalryWith, FC Bern]
-
A.
SC Bern
SC Bern is a professional ice hockey club from Bern, Switzerland, known as one of the country’s most successful and popular teams.
-
B.
FC Baden
FC Baden is a Swiss football club known for competing in the national league system and maintaining local rivalries, including one with nearby club FC Aarau.
-
C.
KFC Uerdingen 05
KFC Uerdingen 05 is a German football club known for its history in the Bundesliga and domestic cup competitions.
-
D.
FC Augsburg
FC Augsburg is a professional German football club based in Augsburg, Bavaria, that competes in the Bundesliga.
-
E.
SC Freiburg
SC Freiburg is a German professional football club based in Freiburg im Breisgau, best known for its Bundesliga participation and strong emphasis on developing young talent.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: FC Bern Triple: [FC Thun, hasRivalryWith, FC Bern]
Generated description
FC Bern is a Swiss football club based in the city of Bern, historically competing in the national league system and known for its local rivalries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FC Bern Target entity description: FC Bern is a Swiss football club based in the city of Bern, historically competing in the national league system and known for its local rivalries.
-
A.
SC Bern
SC Bern is a professional ice hockey club from Bern, Switzerland, known as one of the country’s most successful and popular teams.
-
B.
FC Baden
FC Baden is a Swiss football club known for competing in the national league system and maintaining local rivalries, including one with nearby club FC Aarau.
-
C.
KFC Uerdingen 05
KFC Uerdingen 05 is a German football club known for its history in the Bundesliga and domestic cup competitions.
-
D.
FC Augsburg
FC Augsburg is a professional German football club based in Augsburg, Bavaria, that competes in the Bundesliga.
-
E.
SC Freiburg
SC Freiburg is a German professional football club based in Freiburg im Breisgau, best known for its Bundesliga participation and strong emphasis on developing young talent.
- F. None of above. chosen
Provenance (5 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4871a2130819081743ae89dddc64b |
completed | April 19, 2026, 7:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02efc7a3388190bc13861033cb04f3 |
completed | May 12, 2026, 9:15 a.m. |
| NEDg | Description generation | batch_6a02f08892e08190a75c4e523366feda |
completed | May 12, 2026, 9:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a02f18036788190ad1a2893fd104261 |
completed | May 12, 2026, 9:23 a.m. |
Created at: April 10, 2026, 10:12 a.m.