Triple
T1536849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Dakota |
E32568
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Watertown
Watertown is a principal city in northeastern South Dakota known as a regional commercial center and home to Lake Kampeska and the Redlin Art Center.
|
E848326
|
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: Watertown | Statement: [South Dakota, hasMajorCity, Watertown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Watertown Context triple: [South Dakota, hasMajorCity, Watertown]
-
A.
Watertown, Massachusetts
Watertown, Massachusetts is a historic suburban city just west of Boston, known for its early industrial development and significant Armenian-American community.
-
B.
Fitchburg
Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
-
C.
Lowell
Lowell is a surname most prominently associated with former Major League Baseball third baseman and World Series MVP Mike Lowell.
-
D.
Pittsfield
Pittsfield is a small town located within Otsego County in the central region of New York State.
-
E.
Burlington
Burlington is a historic city in present-day New Jersey that once served as the colonial capital of the Province of New Jersey.
- 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: Watertown Triple: [South Dakota, hasMajorCity, Watertown]
Generated description
Watertown is a principal city in northeastern South Dakota known as a regional commercial center and home to Lake Kampeska and the Redlin Art Center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Watertown Target entity description: Watertown is a principal city in northeastern South Dakota known as a regional commercial center and home to Lake Kampeska and the Redlin Art Center.
-
A.
Watertown, Massachusetts
Watertown, Massachusetts is a historic suburban city just west of Boston, known for its early industrial development and significant Armenian-American community.
-
B.
Fitchburg
Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
-
C.
Lowell
Lowell is a surname most prominently associated with former Major League Baseball third baseman and World Series MVP Mike Lowell.
-
D.
Pittsfield
Pittsfield is a small town located within Otsego County in the central region of New York State.
-
E.
Burlington
Burlington is a small city in southeastern Wisconsin known for its historic downtown, chocolate festival, and role as a local commercial and community hub.
- 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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90829e60081909d3f9f79585e080e |
completed | March 5, 2026, 4:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3549788608190a1949eb254e43a8e |
completed | April 6, 2026, 6:37 a.m. |
| NEDg | Description generation | batch_69d356211fd8819089db018473b959e9 |
completed | April 6, 2026, 6:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d356a1c48c81909820ad66d96c9cc5 |
completed | April 6, 2026, 6:45 a.m. |
Created at: March 4, 2026, 7:26 p.m.