Triple
T3653834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gateway Cities |
E77482
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Cudahy |
E266617
|
NE FINISHED |
How this triple was built (2 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: Cudahy | Statement: [Gateway Cities, hasCity, Cudahy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cudahy Context triple: [Gateway Cities, hasCity, Cudahy]
-
A.
Cudahy
chosen
Cudahy is a small, densely populated city in southeastern Los Angeles County, California, known for its predominantly Latino community and urban residential character.
-
B.
Bayfield
Bayfield is a residential suburb of the historic town of Chepstow in Monmouthshire, Wales.
-
C.
City of Cudahy
The City of Cudahy is a small industrial and residential suburb located just south of Milwaukee in southeastern Wisconsin.
-
D.
Calumet Heights
Calumet Heights is a primarily residential neighborhood located on the South Side of Chicago, known for its stable middle-class character and well-kept homes.
-
E.
Hartland
Hartland is a small rural town in northwestern Connecticut known for its forests, reservoirs, and low population density.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3b9164c81908938a4338430d193 |
completed | March 8, 2026, 6:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4883bb50c8190bd383b21ac748a2e |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:24 p.m.