Triple
T16970296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray Mac Stadium |
E411653
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
Ray Mac
Ray Mac is the commonly used abbreviated name for Ray Mac Stadium, a sports venue.
|
E1243140
|
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: Ray Mac | Statement: [Ray Mac Stadium, shortName, Ray Mac]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ray Mac Context triple: [Ray Mac Stadium, shortName, Ray Mac]
-
A.
David MacQueen
David MacQueen is a computer scientist known for his influential work on the design and formal definition of the Standard ML programming language.
-
B.
Ray McKinnon
Ray McKinnon is an American actor, writer, producer, and director known for his character roles in film and television and for creating the acclaimed series "Rectify."
-
C.
Russell Mack
Russell Mack was an American film director active in early Hollywood, best known for his work on 1930s comedies and stage-to-screen adaptations.
-
D.
Roy McFarland
Roy McFarland is a former English central defender best known for his key role in Derby County’s successful teams of the late 1960s and 1970s and for earning numerous caps for the England national team.
-
E.
Rick MacLeish
Rick MacLeish was a high-scoring Canadian center best known for his key offensive role on the Philadelphia Flyers’ Stanley Cup–winning teams of the 1970s.
- 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: Ray Mac Triple: [Ray Mac Stadium, shortName, Ray Mac]
Generated description
Ray Mac is the commonly used abbreviated name for Ray Mac Stadium, a sports venue.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ray Mac Target entity description: Ray Mac is the commonly used abbreviated name for Ray Mac Stadium, a sports venue.
-
A.
David MacQueen
David MacQueen is a computer scientist known for his influential work on the design and formal definition of the Standard ML programming language.
-
B.
Ray McKinnon
Ray McKinnon is an American actor, writer, producer, and director known for his character roles in film and television and for creating the acclaimed series "Rectify."
-
C.
Russell Mack
Russell Mack was an American film director active in early Hollywood, best known for his work on 1930s comedies and stage-to-screen adaptations.
-
D.
Roy McFarland
Roy McFarland is a former English central defender best known for his key role in Derby County’s successful teams of the late 1960s and 1970s and for earning numerous caps for the England national team.
-
E.
Rick MacLeish
Rick MacLeish was a high-scoring Canadian center best known for his key offensive role on the Philadelphia Flyers’ Stanley Cup–winning teams of the 1970s.
- F. None of above. chosen
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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0ac23a48190992fa125fceb1eb2 |
completed | April 18, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d471d4248190acf40b6c11926a65 |
completed | May 10, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_6a00d503f4f08190a0dcdb050d5bc7a3 |
completed | May 10, 2026, 6:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d5adee908190a13bfc765e7c8f06 |
completed | May 10, 2026, 6:59 p.m. |
Created at: April 10, 2026, 5:31 a.m.