Triple
T622867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stockholm |
E14550
|
entity |
| Predicate | river |
P165
|
FINISHED |
| Object |
Norrström
Norrström is a short but significant river in central Stockholm that connects Lake Mälaren with the Baltic Sea and flows past several of the city’s key historic and governmental buildings.
|
E78000
|
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: Norrström | Statement: [Stockholm, river, Norrström]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norrström Context triple: [Stockholm, river, Norrström]
-
A.
Bäckström
Bäckström is a Swedish surname most prominently associated with NHL ice hockey star Nicklas Bäckström.
-
B.
Svante
Svante is the given name of Swedish geneticist Svante Pääbo, a Nobel Prize–winning pioneer in the field of paleogenomics.
-
C.
Göransson
Göransson is a Swedish surname most notably borne by composer and record producer Ludwig Göransson.
-
D.
Olof
Olof is a Scandinavian male given name, particularly common in Sweden and Norway, derived from Old Norse and borne by various notable historical and cultural figures.
-
E.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
- 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: Norrström Triple: [Stockholm, river, Norrström]
Generated description
Norrström is a short but significant river in central Stockholm that connects Lake Mälaren with the Baltic Sea and flows past several of the city’s key historic and governmental buildings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Norrström Target entity description: Norrström is a short but significant river in central Stockholm that connects Lake Mälaren with the Baltic Sea and flows past several of the city’s key historic and governmental buildings.
-
A.
Bäckström
Bäckström is a Swedish surname most prominently associated with NHL ice hockey star Nicklas Bäckström.
-
B.
Svante
Svante is the given name of Swedish geneticist Svante Pääbo, a Nobel Prize–winning pioneer in the field of paleogenomics.
-
C.
Göransson
Göransson is a Swedish surname most notably borne by composer and record producer Ludwig Göransson.
-
D.
Olof
Olof is a Scandinavian male given name, particularly common in Sweden and Norway, derived from Old Norse and borne by various notable historical and cultural figures.
-
E.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e402d9c8190936896e3ebb6edc5 |
completed | March 1, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a563cab73c819082b51d64d249143b |
completed | March 2, 2026, 10:17 a.m. |
| NEDg | Description generation | batch_69a5657b51c881909c393f79c359181c |
completed | March 2, 2026, 10:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a565e528a88190a547f69c7e378140 |
completed | March 2, 2026, 10:26 a.m. |
Created at: March 1, 2026, 7:35 p.m.