Triple
T10950975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburger SV |
E258723
|
entity |
| Predicate | governingBody |
P46
|
FINISHED |
| Object | DFL |
E185149
|
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: DFL | Statement: [Hamburger SV, governingBody, DFL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DFL Context triple: [Hamburger SV, governingBody, DFL]
-
A.
DFL
chosen
DFL (Deutsche Fußball Liga) is the governing body responsible for operating and marketing Germany’s top professional football leagues.
-
B.
DFLZM
DFLZM is the abbreviated name of Dongfeng Liuzhou Motor, a Chinese automobile manufacturer known for producing commercial vehicles and passenger cars.
-
C.
UFL
UFL is a common abbreviation for the University of Florida, a major public research university in Gainesville known for its strong academics and athletics.
-
D.
LFL
LFL is the former New York Stock Exchange ticker symbol for LAN Airlines, a major Chilean airline that later became part of LATAM Airlines Group.
-
E.
LFL
LFL is the Legends Football League, a women's American football league featuring teams such as the Chicago Bliss.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770fc156c8190826e124c13ce7242 |
completed | April 9, 2026, 9:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e23c57038c819087671177c2ed5633 |
completed | April 17, 2026, 1:57 p.m. |
Created at: April 8, 2026, 9:23 p.m.