Triple
T22940608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waterbury, Connecticut |
E569717
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | The Brass City |
—
|
NE NERFINISHED |
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: The Brass City | Statement: [Waterbury, Connecticut, nickname, The Brass City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Brass City Context triple: [Waterbury, Connecticut, nickname, The Brass City]
-
A.
The Brass City
chosen
The Brass City is a nickname for Waterbury, Connecticut, reflecting its historic prominence in brass manufacturing and metalworking.
-
B.
Brass City
Brass City is the popular nickname for Moradabad, an Indian city renowned for its large-scale brass handicraft and metalware industry.
-
C.
Steel City
Steel City is a common nickname for Hamilton, Ontario, reflecting its historic role as a major Canadian center of steel production and heavy industry.
-
D.
Steel City
Steel City is a nickname for Lorain, Ohio, reflecting its historic role as a major center of steel production and heavy industry.
-
E.
Steel City
Steel City is a nickname for the industrial city of Salem, reflecting its historical association with steel production and metalworking.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24590862c8190858f180ad302adab |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1813844b88190b05d3829b0c423c4 |
completed | April 29, 2026, 3:55 a.m. |
Created at: April 17, 2026, 3:45 p.m.