Triple
T9214549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Statens Museum for Kunst |
E221209
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
SMK
SMK is Denmark’s national gallery in Copenhagen, renowned for its extensive collection of Danish and international art from the Renaissance to the present.
|
E785530
|
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: SMK | Statement: [Statens Museum for Kunst, shortName, SMK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SMK Context triple: [Statens Museum for Kunst, shortName, SMK]
-
A.
SMK
SMK is the commonly used abbreviation for the Office of the Prime Minister of Norway, the central executive body that supports the Norwegian Prime Minister and coordinates government policy.
-
B.
SMWK
SMWK is the abbreviation for the Saxon State Ministry responsible for science, culture, and tourism in the German state of Saxony.
-
C.
SM
SM is the vehicle registration code used on license plates for the city of Sremska Mitrovica in Serbia.
-
D.
SMO
SMO is the IATA airport code for Santa Monica Airport, a general aviation facility located in Santa Monica, California.
-
E.
SMCC
SMCC is the acronym for the Shanghai Municipal Commerce Commission, the government body responsible for overseeing and promoting commerce and trade in Shanghai.
- 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: SMK Triple: [Statens Museum for Kunst, shortName, SMK]
Generated description
SMK is Denmark’s national gallery in Copenhagen, renowned for its extensive collection of Danish and international art from the Renaissance to the present.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SMK Target entity description: SMK is Denmark’s national gallery in Copenhagen, renowned for its extensive collection of Danish and international art from the Renaissance to the present.
-
A.
SMK
SMK is the commonly used abbreviation for the Office of the Prime Minister of Norway, the central executive body that supports the Norwegian Prime Minister and coordinates government policy.
-
B.
SMWK
SMWK is the abbreviation for the Saxon State Ministry responsible for science, culture, and tourism in the German state of Saxony.
-
C.
SM
SM is the vehicle registration code used on license plates for the city of Sremska Mitrovica in Serbia.
-
D.
SMO
SMO is the IATA airport code for Santa Monica Airport, a general aviation facility located in Santa Monica, California.
-
E.
SMCC
SMCC is the acronym for the Shanghai Municipal Commerce Commission, the government body responsible for overseeing and promoting commerce and trade in Shanghai.
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda06bf80819094c6e74b4b6a31e4 |
completed | April 1, 2026, 8:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d06613daf88190a0128fd53ea1b134 |
completed | April 4, 2026, 1:15 a.m. |
| NEDg | Description generation | batch_69d0678b89ac8190b807e1c3b457a503 |
completed | April 4, 2026, 1:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0688d4c388190bb024b03cc86d08f |
completed | April 4, 2026, 1:25 a.m. |
Created at: March 30, 2026, 7:27 p.m.