Triple
T7080932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Changchun |
E164950
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Automobile City
Automobile City is a nickname for Changchun, a major Chinese industrial center renowned as one of the country’s leading hubs of automobile manufacturing.
|
E641200
|
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: Automobile City | Statement: [Changchun, nickname, Automobile City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Automobile City Context triple: [Changchun, nickname, Automobile City]
-
A.
Ford City
Ford City is a small borough in western Pennsylvania known historically as an industrial company town along the Allegheny River.
-
B.
Metro City
Metro City is the fictional, superhero-populated metropolis that serves as the primary setting of the animated film "Megamind."
-
C.
The Garden City
The Garden City is a nickname for Newton, Massachusetts, reflecting its abundant green spaces, tree-lined streets, and residential charm.
-
D.
The Garden City
The Garden City is a nickname for St. Catharines, a city in Ontario, Canada known for its abundant parks, green spaces, and floral beauty.
-
E.
The Garden City
The Garden City is a popular nickname for Christchurch, New Zealand, highlighting its extensive parks, gardens, and tree-lined streets.
- 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: Automobile City Triple: [Changchun, nickname, Automobile City]
Generated description
Automobile City is a nickname for Changchun, a major Chinese industrial center renowned as one of the country’s leading hubs of automobile manufacturing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Automobile City Target entity description: Automobile City is a nickname for Changchun, a major Chinese industrial center renowned as one of the country’s leading hubs of automobile manufacturing.
-
A.
Ford City
Ford City is a small borough in western Pennsylvania known historically as an industrial company town along the Allegheny River.
-
B.
Metro City
Metro City is the fictional, superhero-populated metropolis that serves as the primary setting of the animated film "Megamind."
-
C.
The Garden City
The Garden City is a nickname for Newton, Massachusetts, reflecting its abundant green spaces, tree-lined streets, and residential charm.
-
D.
The Garden City
The Garden City is a nickname for St. Catharines, a city in Ontario, Canada known for its abundant parks, green spaces, and floral beauty.
-
E.
The Garden City
The Garden City is a popular nickname for Christchurch, New Zealand, highlighting its extensive parks, gardens, and tree-lined streets.
- 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_69c6887cbc6c8190bdfac42d940f4d8a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4f1f5748190b214856bcfc70d81 |
completed | March 27, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79477a79c81909b51175a24d17142 |
completed | March 28, 2026, 8:42 a.m. |
| NEDg | Description generation | batch_69c798cd9e4c8190a9dc1176d60d2cf6 |
completed | March 28, 2026, 9:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c799fae8608190b0cd94d59ab589a4 |
completed | March 28, 2026, 9:06 a.m. |
Created at: March 27, 2026, 2:40 p.m.