Triple
T20669692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Werner Lorant |
E507986
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object |
FC Senec
FC Senec was a Slovak football club that competed in the country’s top divisions before eventually merging and disappearing from professional play.
|
E1444744
|
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 Senec | Statement: [Werner Lorant, employer, FC Senec]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FC Senec Context triple: [Werner Lorant, employer, FC Senec]
-
A.
Laurin & Klement FC
Laurin & Klement FC is an early automobile model produced by the Czech manufacturer Laurin & Klement, a predecessor of Škoda Auto.
-
B.
FC Kuřim
FC Kuřim is a Czech football club based in the town of Kuřim.
-
C.
FC Hradec Králové
FC Hradec Králové is a Czech professional football club based in the city of Hradec Králové that competes in the country’s top leagues and national competitions.
-
D.
HC Frýdek-Místek
HC Frýdek-Místek is a Czech ice hockey club that serves as the farm team for the top-tier Extraliga side HC Oceláři Třinec.
-
E.
FC Sens
FC Sens is a French football club representing the town of Sens in regional and national competitions.
- 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 Senec Triple: [Werner Lorant, employer, FC Senec]
Generated description
FC Senec was a Slovak football club that competed in the country’s top divisions before eventually merging and disappearing from professional play.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FC Senec Target entity description: FC Senec was a Slovak football club that competed in the country’s top divisions before eventually merging and disappearing from professional play.
-
A.
Laurin & Klement FC
Laurin & Klement FC is an early automobile model produced by the Czech manufacturer Laurin & Klement, a predecessor of Škoda Auto.
-
B.
FC Kuřim
FC Kuřim is a Czech football club based in the town of Kuřim.
-
C.
FC Hradec Králové
FC Hradec Králové is a Czech professional football club based in the city of Hradec Králové that competes in the country’s top leagues and national competitions.
-
D.
HC Frýdek-Místek
HC Frýdek-Místek is a Czech ice hockey club that serves as the farm team for the top-tier Extraliga side HC Oceláři Třinec.
-
E.
FC Sens
FC Sens is a French football club representing the town of Sens in regional and national competitions.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5c735048190a01cb7692928d66e |
completed | April 20, 2026, 11:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08cd64aa4081908cf843a32e99ae01 |
completed | May 16, 2026, 8:02 p.m. |
| NEDg | Description generation | batch_6a08d175eefc8190a5178c0f70f7d79f |
completed | May 16, 2026, 8:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08d23e8ac48190be1726c8e4913b1a |
completed | May 16, 2026, 8:23 p.m. |
Created at: April 16, 2026, 11:44 a.m.