Triple
T38136194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toronto Maple Leafs (International League) |
E952358
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object |
Lol Solman
Lol Solman was a sports executive best known for owning the Toronto Maple Leafs baseball team in the International League.
|
E2258046
|
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: Lol Solman | Statement: [Toronto Maple Leafs (International League), owner, Lol Solman]
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: Lol Solman Triple: [Toronto Maple Leafs (International League), owner, Lol Solman]
Generated description
Lol Solman was a sports executive best known for owning the Toronto Maple Leafs baseball team in the International League.
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_69f76f09a7148190a4b91c0bacdc127a |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc4606af388190864b27fa60c202c1 |
completed | May 7, 2026, 7:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a417126c5f48190b4bb8f4cd2cbdb84 |
completed | June 28, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_6a4173143a308190828a5cb1be6e4f2d |
completed | June 28, 2026, 7:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a41738d9b508190ad95d1f67ce42904 |
completed | June 28, 2026, 7:18 p.m. |
Created at: May 3, 2026, 4:21 p.m.