Triple
T14496814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bruce Kimmel |
E359521
|
entity |
| Predicate | recordLabel |
P1500
|
FINISHED |
| Object |
Bay Cities
Bay Cities was a niche American record label known for releasing film scores, cast recordings, and other specialty soundtrack and theater-related albums.
|
E1103212
|
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: Bay Cities | Statement: [Bruce Kimmel, recordLabel, Bay Cities]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bay Cities Context triple: [Bruce Kimmel, recordLabel, Bay Cities]
-
A.
Ice City
Ice City is the popular nickname for Harbin, a major northeastern Chinese city renowned for its frigid winters and spectacular ice and snow sculptures.
-
B.
Bell City
Bell City is a nickname for Bristol, Connecticut, historically known for its prominent clock and bell manufacturing industry.
-
C.
Spring City
Spring City is the popular nickname of Kunming, the capital of Yunnan Province in China, renowned for its mild, spring-like climate year-round.
-
D.
Spring City
Spring City is a nickname for Waukesha, Wisconsin, reflecting its historic abundance of natural springs.
-
E.
Sunrise City
Sunrise City is the coastal Florida city of Fort Pierce, known for its picturesque Atlantic Ocean sunrises and historic waterfront charm.
- 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: Bay Cities Triple: [Bruce Kimmel, recordLabel, Bay Cities]
Generated description
Bay Cities was a niche American record label known for releasing film scores, cast recordings, and other specialty soundtrack and theater-related albums.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bay Cities Target entity description: Bay Cities was a niche American record label known for releasing film scores, cast recordings, and other specialty soundtrack and theater-related albums.
-
A.
Ice City
Ice City is the popular nickname for Harbin, a major northeastern Chinese city renowned for its frigid winters and spectacular ice and snow sculptures.
-
B.
Bell City
Bell City is a nickname for Bristol, Connecticut, historically known for its prominent clock and bell manufacturing industry.
-
C.
Spring City
Spring City is the popular nickname of Kunming, the capital of Yunnan Province in China, renowned for its mild, spring-like climate year-round.
-
D.
Spring City
Spring City is a nickname for Waukesha, Wisconsin, reflecting its historic abundance of natural springs.
-
E.
Sunrise City
Sunrise City is the coastal Florida city of Fort Pierce, known for its picturesque Atlantic Ocean sunrises and historic waterfront charm.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de93109cb081909a6e846db23a4635 |
completed | April 14, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d9731588190b27a826582e5fc6d |
completed | May 8, 2026, 4:59 a.m. |
| NEDg | Description generation | batch_69fd6f82453481909a3e1b032f30a7a5 |
completed | May 8, 2026, 5:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd708521c881909863b7cd3fc4a313 |
completed | May 8, 2026, 5:11 a.m. |
Created at: April 10, 2026, 1:21 a.m.