Triple
T8447357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diana Prince |
E199708
|
entity |
| Predicate | baseOfOperations |
P2591
|
FINISHED |
| Object |
Gateway City
Gateway City is a fictional American metropolis in DC Comics best known as one of Wonder Woman’s primary cities of operation.
|
E733912
|
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: Gateway City | Statement: [Diana Prince, baseOfOperations, Gateway City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gateway City Context triple: [Diana Prince, baseOfOperations, Gateway City]
-
A.
Gateway City
Gateway City is a nickname for St. Louis, Missouri, highlighting its historic role as a major entry point to the American West.
-
B.
Hat City
Hat City is the nickname of Danbury, Connecticut, reflecting its historic prominence as a major center of hat manufacturing in the United States.
-
C.
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.
-
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. 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: Gateway City Triple: [Diana Prince, baseOfOperations, Gateway City]
Generated description
Gateway City is a fictional American metropolis in DC Comics best known as one of Wonder Woman’s primary cities of operation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gateway City Target entity description: Gateway City is a fictional American metropolis in DC Comics best known as one of Wonder Woman’s primary cities of operation.
-
A.
Gateway City
Gateway City is a nickname for St. Louis, Missouri, highlighting its historic role as a major entry point to the American West.
-
B.
Hat City
Hat City is the nickname of Danbury, Connecticut, reflecting its historic prominence as a major center of hat manufacturing in the United States.
-
C.
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.
-
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. 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44480ec8190b32443a53cd4f943 |
completed | March 31, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1db6330c81909c853c453fddf3c5 |
completed | April 2, 2026, 7:41 a.m. |
| NEDg | Description generation | batch_69ce1ea3aaf881909562b65cefb20089 |
completed | April 2, 2026, 7:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce1f8d748c81909b331ed822919447 |
completed | April 2, 2026, 7:49 a.m. |
Created at: March 30, 2026, 6:09 p.m.