Triple
T37398210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orchard Lake St. Mary’s campus |
E928916
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object |
Orchard Lake Schools
Orchard Lake Schools is a private Catholic educational complex in Orchard Lake, Michigan, encompassing secondary and higher education institutions with strong Polish-American and religious traditions.
|
E2225135
|
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: Orchard Lake Schools | Statement: [Orchard Lake St. Mary’s campus, partOf, Orchard Lake Schools]
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: Orchard Lake Schools Triple: [Orchard Lake St. Mary’s campus, partOf, Orchard Lake Schools]
Generated description
Orchard Lake Schools is a private Catholic educational complex in Orchard Lake, Michigan, encompassing secondary and higher education institutions with strong Polish-American and religious traditions.
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_69f76ebb10c481909b54b9dba263e29f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb8d5a6eac819096b964b31df81b88 |
completed | May 6, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a4077055f588190baff46bf7ddf04ac |
completed | June 28, 2026, 1:21 a.m. |
| NEDg | Description generation | batch_6a4077c183048190b60204779b4336b5 |
completed | June 28, 2026, 1:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a4078362d0881909b963ee3fe45787e |
completed | June 28, 2026, 1:26 a.m. |
Created at: May 3, 2026, 4:16 p.m.