Triple
T23168220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Glass City |
E578770
|
entity |
| Predicate | hasAlternativeForm |
P455
|
FINISHED |
| Object | Glass 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: Glass City | Statement: [The Glass City, hasAlternativeForm, Glass City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glass City Context triple: [The Glass City, hasAlternativeForm, Glass City]
-
A.
Glass City
chosen
Glass City is a nickname for Toledo, Ohio, reflecting its historic prominence in the glass manufacturing industry.
-
B.
Glass City
Glass City is a nickname commonly associated with Westland, likely referencing its historical or industrial ties to glass production or glass-related manufacturing.
-
C.
Brick City
Brick City is a nickname commonly used for Newark, New Jersey, known for its dense urban landscape and prominent role in hip-hop culture.
-
D.
River City
River City is a popular nickname for Sacramento, California, highlighting the city’s close connection to the nearby American and Sacramento Rivers.
-
E.
River City
River City is a popular nickname for Wuhan, a major central Chinese metropolis known for its location at the confluence of the Yangtze and Han rivers.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f2d51288190af0d5747090d8e5d |
completed | April 29, 2026, 4:55 a.m. |
Created at: April 17, 2026, 4:03 p.m.