Triple
T9168033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Munkkiniemi |
E220012
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Haaga
Haaga is a residential district in western Helsinki, Finland, known for its parks, including the popular rhododendron garden, and good public transport connections.
|
E782392
|
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: Haaga | Statement: [Munkkiniemi, locatedNear, Haaga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haaga Context triple: [Munkkiniemi, locatedNear, Haaga]
-
A.
Harjola
Harjola is a Finnish surname, notably borne by film director Renny Harlin (born Lauri Mauritz Harjola).
-
B.
Hassela
Hassela is a small rural locality in northern Sweden known for its forested landscape and nearby ski and outdoor recreation areas.
-
C.
Hassel
Hassel is a Norwegian surname most notably borne by Nobel Prize–winning chemist Odd Hassel.
-
D.
Hå
Hå is a coastal municipality in southwestern Norway known for its agricultural landscape, beaches, and location along the North Sea in Rogaland county.
-
E.
Harauti
Harauti is an Indo-Aryan dialect of the Rajasthani language spoken primarily in the Hadoti region of Rajasthan, India.
- 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: Haaga Triple: [Munkkiniemi, locatedNear, Haaga]
Generated description
Haaga is a residential district in western Helsinki, Finland, known for its parks, including the popular rhododendron garden, and good public transport connections.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Haaga Target entity description: Haaga is a residential district in western Helsinki, Finland, known for its parks, including the popular rhododendron garden, and good public transport connections.
-
A.
Harjola
Harjola is a Finnish surname, notably borne by film director Renny Harlin (born Lauri Mauritz Harjola).
-
B.
Hassela
Hassela is a small rural locality in northern Sweden known for its forested landscape and nearby ski and outdoor recreation areas.
-
C.
Hassel
Hassel is a Norwegian surname most notably borne by Nobel Prize–winning chemist Odd Hassel.
-
D.
Hå
Hå is a coastal municipality in southwestern Norway known for its agricultural landscape, beaches, and location along the North Sea in Rogaland county.
-
E.
Harauti
Harauti is an Indo-Aryan dialect of the Rajasthani language spoken primarily in the Hadoti region of Rajasthan, India.
- 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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaadfb50881909b9127f92e4b3e21 |
completed | April 1, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05491ccec819093fcf2d764c5381b |
completed | April 4, 2026, midnight |
| NEDg | Description generation | batch_69d05628d8708190a85437c5051a5a05 |
completed | April 4, 2026, 12:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d056e4ad98819086e73edf15aa6210 |
completed | April 4, 2026, 12:10 a.m. |
Created at: March 30, 2026, 7:22 p.m.