Triple
T1596981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dracut |
E34304
|
entity |
| Predicate | hasHistoricArea |
P5057
|
FINISHED |
| Object |
Kenwood
Kenwood is a historic neighborhood within Dracut, Massachusetts, known for its preserved architecture and local heritage.
|
E181587
|
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: Kenwood | Statement: [Dracut, hasHistoricArea, Kenwood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenwood Context triple: [Dracut, hasHistoricArea, Kenwood]
-
A.
Kenwood
Kenwood is a small community in California’s Sonoma Valley known for its wineries, vineyards, and scenic rural charm.
-
B.
Nagata Acoustics
Nagata Acoustics is a renowned Japanese acoustic consulting firm known worldwide for designing the sound environments of major concert halls and performing arts centers.
-
C.
Bose
Bose is a common Indian surname most prominently associated with physicist Satyendra Nath Bose, whose work led to the concept of bosons and Bose–Einstein statistics.
-
D.
Panasonic
Panasonic is a major Japanese multinational electronics company known for its wide range of consumer electronics, home appliances, and industrial solutions.
-
E.
Telefunken
Telefunken is a historic German electronics and television brand known for its radios, audio equipment, and consumer electronics.
- 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: Kenwood Triple: [Dracut, hasHistoricArea, Kenwood]
Generated description
Kenwood is a historic neighborhood within Dracut, Massachusetts, known for its preserved architecture and local heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kenwood Target entity description: Kenwood is a historic neighborhood within Dracut, Massachusetts, known for its preserved architecture and local heritage.
-
A.
Kenwood
Kenwood is a small community in California’s Sonoma Valley known for its wineries, vineyards, and scenic rural charm.
-
B.
Nagata Acoustics
Nagata Acoustics is a renowned Japanese acoustic consulting firm known worldwide for designing the sound environments of major concert halls and performing arts centers.
-
C.
Bose
Bose is a common Indian surname most prominently associated with physicist Satyendra Nath Bose, whose work led to the concept of bosons and Bose–Einstein statistics.
-
D.
Panasonic
Panasonic is a major Japanese multinational electronics company known for its wide range of consumer electronics, home appliances, and industrial solutions.
-
E.
Telefunken
Telefunken is a historic German electronics and television brand known for its radios, audio equipment, and consumer electronics.
- 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9092e46748190b27be7d1aba07dff |
completed | March 5, 2026, 4:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad46a848ec819085c82be8eaea2044 |
completed | March 8, 2026, 9:51 a.m. |
| NEDg | Description generation | batch_69ad4841d278819085507528faeaae3e |
completed | March 8, 2026, 9:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad48ff11d881909fd6e9e40d5f1f38 |
completed | March 8, 2026, 10:01 a.m. |
Created at: March 4, 2026, 7:27 p.m.