Triple
T6149049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stabæk Fotball |
E137150
|
entity |
| Predicate | hasWon |
P2624
|
FINISHED |
| Object | Eliteserien |
E119741
|
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: Eliteserien | Statement: [Stabæk Fotball, hasWon, Eliteserien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eliteserien Context triple: [Stabæk Fotball, hasWon, Eliteserien]
-
A.
Eliteserien
chosen
Eliteserien is the top professional football league in Norway, featuring the country’s highest-level clubs in the sport.
-
B.
Norwegian First Division
The Norwegian First Division is the second-highest level of professional football in Norway, sitting directly below the top-tier Eliteserien.
-
C.
Norwegian Toppserien
Norwegian Toppserien is the top-tier professional women's football league in Norway.
-
D.
Superettan
Superettan is the second-highest professional football league in Sweden, sitting directly below the Allsvenskan in the national league system.
-
E.
Erovnuli Liga
Erovnuli Liga is the top professional football division in Georgia, featuring the country’s leading clubs in its premier league competition.
- 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_69c008a2c6308190a56519b22d55d083 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05ce21820819096be9159d6b70a5f |
completed | March 22, 2026, 9:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1417c33d08190bd42558cc734601f |
completed | March 23, 2026, 1:34 p.m. |
Created at: March 22, 2026, 4:16 p.m.