Triple
T3752967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wakefield, Massachusetts |
E81374
|
entity |
| Predicate | hasNeighborhood |
P40
|
FINISHED |
| Object |
Lakeside
Lakeside is a residential neighborhood in the city of Wakefield, Massachusetts, known for its proximity to the town’s lakes and local amenities.
|
E385464
|
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: Lakeside | Statement: [Wakefield, Massachusetts, hasNeighborhood, Lakeside]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lakeside Context triple: [Wakefield, Massachusetts, hasNeighborhood, Lakeside]
-
A.
Lakeside
Lakeside is a small settlement in England’s Lake District, known as a lakeside stop and tourist base on the southern shore of Windermere.
-
B.
Lakeside
Lakeside is an upscale seafood restaurant at the Wynn Las Vegas known for its lakefront views and fine dining experience.
-
C.
Lakeside
Lakeside is a suburban community in Henrico County, Virginia, known for its residential neighborhoods and proximity to the city of Richmond.
-
D.
City of Lakes
City of Lakes is a popular nickname for Minneapolis, highlighting its many urban lakes and waterfronts.
-
E.
City of Lakes
City of Lakes is a popular nickname for Udaipur, a picturesque city in Rajasthan, India, renowned for its numerous interconnected lakes and romantic waterfront scenery.
- 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: Lakeside Triple: [Wakefield, Massachusetts, hasNeighborhood, Lakeside]
Generated description
Lakeside is a residential neighborhood in the city of Wakefield, Massachusetts, known for its proximity to the town’s lakes and local amenities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lakeside Target entity description: Lakeside is a residential neighborhood in the city of Wakefield, Massachusetts, known for its proximity to the town’s lakes and local amenities.
-
A.
Lakeside
Lakeside is an upscale seafood restaurant at the Wynn Las Vegas known for its lakefront views and fine dining experience.
-
B.
Lakeside
Lakeside is a small settlement in England’s Lake District, known as a lakeside stop and tourist base on the southern shore of Windermere.
-
C.
Lakeside
Lakeside is a suburban community in Henrico County, Virginia, known for its residential neighborhoods and proximity to the city of Richmond.
-
D.
City of Lakes
City of Lakes is a popular nickname for Minneapolis, highlighting its many urban lakes and waterfronts.
-
E.
City of Lakes
City of Lakes is a popular nickname for Udaipur, a picturesque city in Rajasthan, India, renowned for its numerous interconnected lakes and romantic waterfront scenery.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb9340e0819083215989718b4598 |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e5044f3c8190969828966b37e729 |
completed | March 14, 2026, 4:33 a.m. |
| NEDg | Description generation | batch_69b4e587f8588190bf3a1c744433619b |
completed | March 14, 2026, 4:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4e61dc8bc81909b683e54cd4ca2f6 |
completed | March 14, 2026, 4:37 a.m. |
Created at: March 8, 2026, 3:35 p.m.