Triple
T13801045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SM-sarja |
E331639
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | SM-sarja |
E331639
|
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: SM-sarja | Statement: [SM-sarja, shortName, SM-sarja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SM-sarja Context triple: [SM-sarja, shortName, SM-sarja]
-
A.
SM-sarja
chosen
SM-sarja was the top-level Finnish ice hockey league that preceded and was later replaced by the modern SM-liiga.
-
B.
SM
SM is the vehicle registration code used on license plates for the city of Sremska Mitrovica in Serbia.
-
C.
SV
SV is the two-letter ISO 3166-1 alpha-2 country code assigned to El Salvador.
-
D.
SV
SV is the official abbreviation for the Slovenian Armed Forces, the military organization responsible for defending the Republic of Slovenia.
-
E.
SV
SV is the commonly used abbreviation for the Faculty of Social Sciences at the University of Oslo, encompassing disciplines such as sociology, political science, economics, and related fields.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de025ded6c8190851c108ae559a355 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b0893a20819081d4001b8dbc9c36 |
completed | May 3, 2026, 8:31 p.m. |
Created at: April 9, 2026, 10:11 p.m.