Triple
T13664842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | central Vermont |
E327090
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Waterbury
Waterbury is a small Vermont town known for its scenic Green Mountain setting, outdoor recreation, and attractions like the Ben & Jerry’s ice cream factory.
|
E1481591
|
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: Waterbury | Statement: [central Vermont, contains, Waterbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waterbury Context triple: [central Vermont, contains, Waterbury]
-
A.
Waterbury
Waterbury is a historic industrial city in western Connecticut known for its former prominence in brass manufacturing and its nickname "The Brass City."
-
B.
Naugatuck
Naugatuck is a borough and town in Connecticut known for its industrial history and location along the Naugatuck River.
-
C.
Meriden
Meriden is a village and civil parish in the West Midlands of England, historically known as a traditional contender for the geographical centre of England.
-
D.
Meriden
Meriden is a city in central Connecticut known for its historic silver manufacturing industry and landmarks like Castle Craig in Hubbard Park.
-
E.
Hamden
Hamden is a suburban town in south-central Connecticut, known for its proximity to New Haven and as the home of Quinnipiac University.
- 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: Waterbury Triple: [central Vermont, contains, Waterbury]
Generated description
Waterbury is a small Vermont town known for its scenic Green Mountain setting, outdoor recreation, and attractions like the Ben & Jerry’s ice cream factory.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Waterbury Target entity description: Waterbury is a small Vermont town known for its scenic Green Mountain setting, outdoor recreation, and attractions like the Ben & Jerry’s ice cream factory.
-
A.
Waterbury
Waterbury is a historic industrial city in western Connecticut known for its former prominence in brass manufacturing and its nickname "The Brass City."
-
B.
Naugatuck
Naugatuck is a borough and town in Connecticut known for its industrial history and location along the Naugatuck River.
-
C.
Meriden
Meriden is a city in central Connecticut known for its historic silver manufacturing industry and landmarks like Castle Craig in Hubbard Park.
-
D.
Meriden
Meriden is a village and civil parish in the West Midlands of England, historically known as a traditional contender for the geographical centre of England.
-
E.
Hamden
Hamden is a suburban town in south-central Connecticut, known for its proximity to New Haven and as the home of Quinnipiac University.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc622a07c81909ef7fb55e719dd9a |
completed | April 12, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09b40757c881908af169bb49628a28 |
completed | May 17, 2026, 12:26 p.m. |
| NEDg | Description generation | batch_6a09b77e73608190a21675b1bd7b8852 |
completed | May 17, 2026, 12:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09b7e6888c8190ba9c22e38c47a773 |
completed | May 17, 2026, 12:43 p.m. |
Created at: April 9, 2026, 9:52 p.m.