Triple
T3190403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanchang |
E66806
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Hero City
Hero City is the honorary title given to Nanchang, a major city in southeastern China renowned for its pivotal role in the early Chinese revolutionary movement.
|
E336611
|
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: Hero City | Statement: [Nanchang, nickname, Hero City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hero City Context triple: [Nanchang, nickname, Hero City]
-
A.
Archangel City
Archangel City is an alternative name for the Russian port city of Arkhangelsk, a historic hub of Arctic trade and shipbuilding on the White Sea.
-
B.
Star City
Star City is a commonly used nickname for the city of Lincoln, Nebraska.
-
C.
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.
-
D.
Crown City
Crown City is a nickname for Pasadena, California, highlighting its reputation as an elegant, historically rich city known for events like the Rose Parade.
-
E.
Winter City
Winter City is the popular nickname for Östersund, a Swedish town renowned for its cold climate and strong winter sports culture.
- 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: Hero City Triple: [Nanchang, nickname, Hero City]
Generated description
Hero City is the honorary title given to Nanchang, a major city in southeastern China renowned for its pivotal role in the early Chinese revolutionary movement.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hero City Target entity description: Hero City is the honorary title given to Nanchang, a major city in southeastern China renowned for its pivotal role in the early Chinese revolutionary movement.
-
A.
Archangel City
Archangel City is an alternative name for the Russian port city of Arkhangelsk, a historic hub of Arctic trade and shipbuilding on the White Sea.
-
B.
Star City
Star City is a commonly used nickname for the city of Lincoln, Nebraska.
-
C.
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.
-
D.
Crown City
Crown City is a nickname for Pasadena, California, highlighting its reputation as an elegant, historically rich city known for events like the Rose Parade.
-
E.
Winter City
Winter City is the popular nickname for Östersund, a Swedish town renowned for its cold climate and strong winter sports culture.
- 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_69ad8588ba18819086a10951c32ecb80 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6e7d0d081908b1c36bb909a58bf |
completed | March 8, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b24b9a9bc88190b7090bda8fe6260c |
completed | March 12, 2026, 5:14 a.m. |
| NEDg | Description generation | batch_69b24d677ca8819094cb03360ac885da |
completed | March 12, 2026, 5:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b25178f3c08190be78bdbd0cdfc5f3 |
completed | March 12, 2026, 5:39 a.m. |
Created at: March 8, 2026, 3:07 p.m.