Triple
T37669571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monroe County, Wisconsin |
E937917
|
entity |
| Predicate | traversedBy |
P225
|
FINISHED |
| Object |
Wisconsin Highway 71
Wisconsin Highway 71 is a state highway in Wisconsin that runs east–west through several counties in the western part of the state, connecting small rural communities and local highways.
|
E2256966
|
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: Wisconsin Highway 71 | Statement: [Monroe County, Wisconsin, traversedBy, Wisconsin Highway 71]
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: Wisconsin Highway 71 Triple: [Monroe County, Wisconsin, traversedBy, Wisconsin Highway 71]
Generated description
Wisconsin Highway 71 is a state highway in Wisconsin that runs east–west through several counties in the western part of the state, connecting small rural communities and local highways.
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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba9e4824081909b69a5d10c876529 |
completed | May 6, 2026, 8:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a4167f11ca481908c659e0878583e65 |
completed | June 28, 2026, 6:29 p.m. |
| NEDg | Description generation | batch_6a416bb629348190a74da4c807a84aab |
completed | June 28, 2026, 6:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a416c59fe448190bfe6cffcc42685a9 |
completed | June 28, 2026, 6:47 p.m. |
Created at: May 3, 2026, 4:18 p.m.