Triple
T17931474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Global Reach Gallery |
E448343
|
entity |
| Predicate | locatedInCity |
P40
|
FINISHED |
| Object |
Dayton
Dayton is a mid-sized city in southwestern Ohio known for its aviation heritage, manufacturing history, and role as a regional cultural and economic center.
|
E82485
|
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: Dayton | Statement: [Global Reach Gallery, locatedInCity, Dayton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dayton Context triple: [Global Reach Gallery, locatedInCity, Dayton]
-
A.
Dayton
Dayton is an unincorporated community and census-designated place located within South Brunswick Township in Middlesex County, New Jersey.
-
B.
Dayton
Dayton is a small town located in the state of Indiana in the United States.
-
C.
Dayton
Dayton is a masculine given name of English origin used both as a first name and a surname.
-
D.
Dayton
Dayton is a small city in Minnesota known for its suburban-rural character and location within the Minneapolis–Saint Paul metropolitan area.
-
E.
Dayton
Dayton is a small city in southeastern Tennessee known historically as the site of the 1925 Scopes "Monkey" Trial.
- 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: Dayton Triple: [Global Reach Gallery, locatedInCity, Dayton]
Generated description
Dayton is a mid-sized city in southwestern Ohio known for its aviation heritage, manufacturing history, and role as a regional cultural and economic center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dayton Target entity description: Dayton is a mid-sized city in southwestern Ohio known for its aviation heritage, manufacturing history, and role as a regional cultural and economic center.
-
A.
Dayton
chosen
Dayton is a mid-sized city in southwestern Ohio known for its historic role in aviation, manufacturing, and research, including its close association with major U.S. Air Force installations.
-
B.
Dayton
Dayton is a small town located in the state of Indiana in the United States.
-
C.
Dayton
Dayton is a small city in Minnesota known for its suburban-rural character and location within the Minneapolis–Saint Paul metropolitan area.
-
D.
Dayton
Dayton is a small city in southeastern Tennessee known historically as the site of the 1925 Scopes "Monkey" Trial.
-
E.
Dayton
Dayton is an unincorporated community and census-designated place located within South Brunswick Township in Middlesex County, New Jersey.
- F. None of above.
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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a552bb848190871251474cc208d5 |
completed | April 19, 2026, 9:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03565564b0819090eac67302810d50 |
completed | May 12, 2026, 4:33 p.m. |
| NEDg | Description generation | batch_6a035737f0688190a5aee60a4e63b367 |
completed | May 12, 2026, 4:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03580bf97881909a4f7eb028362eef |
completed | May 12, 2026, 4:40 p.m. |
Created at: April 10, 2026, 10:20 a.m.