Triple
T1934306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walkman |
E41409
|
entity |
| Predicate | notableModel |
P1503
|
FINISHED |
| Object |
Sony WM-2
The Sony WM-2 is an early, compact cassette Walkman model from the 1980s that helped popularize portable personal music listening.
|
E215021
|
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: Sony WM-2 | Statement: [Walkman, notableModel, Sony WM-2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sony WM-2 Context triple: [Walkman, notableModel, Sony WM-2]
-
A.
WM-21 Sólyom
The WM-21 Sólyom was a Hungarian reconnaissance and light bomber aircraft developed in the late 1930s and operated by Hungary during World War II.
-
B.
Denon Wing
Denon Wing is one of the main wings of the Louvre Museum in Paris, housing many of its most famous artworks, including Leonardo da Vinci’s Mona Lisa.
-
C.
Kenwood
Kenwood is a historic neighborhood within Dracut, Massachusetts, known for its preserved architecture and local heritage.
-
D.
Kenwood
Kenwood is a small community in California’s Sonoma Valley known for its wineries, vineyards, and scenic rural charm.
-
E.
Panasonic
Panasonic is a major Japanese multinational electronics company known for its wide range of consumer electronics, home appliances, and industrial solutions.
- 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: Sony WM-2 Triple: [Walkman, notableModel, Sony WM-2]
Generated description
The Sony WM-2 is an early, compact cassette Walkman model from the 1980s that helped popularize portable personal music listening.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sony WM-2 Target entity description: The Sony WM-2 is an early, compact cassette Walkman model from the 1980s that helped popularize portable personal music listening.
-
A.
WM-21 Sólyom
The WM-21 Sólyom was a Hungarian reconnaissance and light bomber aircraft developed in the late 1930s and operated by Hungary during World War II.
-
B.
Denon Wing
Denon Wing is one of the main wings of the Louvre Museum in Paris, housing many of its most famous artworks, including Leonardo da Vinci’s Mona Lisa.
-
C.
Kenwood
Kenwood is a historic neighborhood within Dracut, Massachusetts, known for its preserved architecture and local heritage.
-
D.
Kenwood
Kenwood is a small community in California’s Sonoma Valley known for its wineries, vineyards, and scenic rural charm.
-
E.
Panasonic
Panasonic is a major Japanese multinational electronics company known for its wide range of consumer electronics, home appliances, and industrial solutions.
- 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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb29b51408190afb2f918814e68c7 |
completed | March 7, 2026, 5:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3f3932081909a72d1022259359e |
completed | March 8, 2026, 10:10 p.m. |
| NEDg | Description generation | batch_69adf472aca881908d99cf5bfcae3094 |
completed | March 8, 2026, 10:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adf50d93c88190aa1cbf96526558b6 |
completed | March 8, 2026, 10:15 p.m. |
Created at: March 4, 2026, 7:35 p.m.