Triple
T1787140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The E.N.D. |
E39417
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Electric City |
E189103
|
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: Electric City | Statement: [The E.N.D., hasPart, Electric City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Electric City Context triple: [The E.N.D., hasPart, Electric City]
-
A.
Electric City
chosen
Electric City is a nickname for Peterborough, Ontario, reflecting its early and prominent use of hydroelectric power and electric streetlights.
-
B.
Chocolate City
Chocolate City is a popular nickname for Washington, D.C., highlighting its historically large and influential African American population and culture.
-
C.
Rocket City
Rocket City is the nickname for Huntsville, Alabama, a city renowned for its pivotal role in U.S. space exploration and rocket development.
-
D.
Paper City
Paper City is the nickname of Holyoke, Massachusetts, reflecting its historic prominence as a major center of paper manufacturing.
-
E.
Glass City
Glass City is a nickname for Toledo, Ohio, reflecting its historic prominence in the glass manufacturing industry.
- 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa650ea238819093a15df6f9d73e2d |
completed | March 6, 2026, 5:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5ce137481909fde04dfa2d6a45a |
completed | March 8, 2026, 5:45 p.m. |
Created at: March 4, 2026, 7:32 p.m.