Triple
T27121620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richfield Township, Lucas County, Ohio |
E687010
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object |
city of Toledo, Ohio
The city of Toledo, Ohio is a major industrial and port city in northwest Ohio on the western end of Lake Erie, known historically for its glass production and automotive industry.
|
E597962
|
NE FINISHED |
How this triple was built (2 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: city of Toledo, Ohio | Statement: [Richfield Township, Lucas County, Ohio, borders, city of Toledo, Ohio]
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: city of Toledo, Ohio Triple: [Richfield Township, Lucas County, Ohio, borders, city of Toledo, Ohio]
Generated description
The city of Toledo, Ohio is a major industrial and port city in northwest Ohio on the western end of Lake Erie, known historically for its glass production and automotive industry.
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_69ef148c2b588190afc15b529f7af845 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f624443ba081909232cb5a4b4f9dc2 |
completed | May 2, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1253770640819092cbca57bec4f4b5 |
completed | May 24, 2026, 1:25 a.m. |
| NEDg | Description generation | batch_6a125bfe29c4819090adb68b0326136b |
completed | May 24, 2026, 2:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a125c5c3c88819088a4a329f5c0aa21 |
completed | May 24, 2026, 2:03 a.m. |
Created at: April 27, 2026, 8:59 a.m.