Triple
T2770040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milwaukee County |
E61432
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
City of Cudahy
The City of Cudahy is a small industrial and residential suburb located just south of Milwaukee in southeastern Wisconsin.
|
E296699
|
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: City of Cudahy | Statement: [Milwaukee County, contains, City of Cudahy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Cudahy Context triple: [Milwaukee County, contains, City of Cudahy]
-
A.
Cudahy
Cudahy is a small, densely populated city in southeastern Los Angeles County, California, known for its predominantly Latino community and urban residential character.
-
B.
Eastland
Eastland is a surname most notably associated with James Eastland, a long-serving and influential U.S. senator from Mississippi.
-
C.
City of Santa Cruz
The City of Santa Cruz is a coastal California city known for its beaches, historic boardwalk amusement park, and vibrant surf and university culture.
-
D.
Hartland
Hartland is a given name most notably borne by American theoretical physicist Hartland Snyder, known for his early work on non-commutative geometry in quantum field theory.
-
E.
Hartland
Hartland is a small rural town in northwestern Connecticut known for its forests, reservoirs, and low population density.
- 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: City of Cudahy Triple: [Milwaukee County, contains, City of Cudahy]
Generated description
The City of Cudahy is a small industrial and residential suburb located just south of Milwaukee in southeastern Wisconsin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: City of Cudahy Target entity description: The City of Cudahy is a small industrial and residential suburb located just south of Milwaukee in southeastern Wisconsin.
-
A.
Cudahy
Cudahy is a small, densely populated city in southeastern Los Angeles County, California, known for its predominantly Latino community and urban residential character.
-
B.
Eastland
Eastland is a surname most notably associated with James Eastland, a long-serving and influential U.S. senator from Mississippi.
-
C.
City of Santa Cruz
The City of Santa Cruz is a coastal California city known for its beaches, historic boardwalk amusement park, and vibrant surf and university culture.
-
D.
Hartland
Hartland is a given name most notably borne by American theoretical physicist Hartland Snyder, known for his early work on non-commutative geometry in quantum field theory.
-
E.
Hartland
Hartland is a small rural town in northwestern Connecticut known for its forests, reservoirs, and low population density.
- 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_69ab4b7cd13481909174bca9809ed259 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd690b24819095647dd4a4f902bb |
completed | March 7, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc05061808190abe709eff7a8c986 |
completed | March 10, 2026, 6:55 a.m. |
| NEDg | Description generation | batch_69afc0b6368081908e2520ac6680a409 |
completed | March 10, 2026, 6:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afc145e61881908c0eeae455b02a78 |
completed | March 10, 2026, 6:59 a.m. |
Created at: March 6, 2026, 9:57 p.m.