Triple
T20656321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marshall Thundering Herd football |
E507634
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
Marshall
Marshall is the college football team representing Marshall University, competing in NCAA Division I as the Thundering Herd.
|
E1443396
|
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: Marshall | Statement: [Marshall Thundering Herd football, shortName, Marshall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marshall Context triple: [Marshall Thundering Herd football, shortName, Marshall]
-
A.
Marshall
Marshall is a common English surname borne by numerous notable figures, including military leaders, politicians, and artists.
-
B.
Marshall
Marshall is a 2017 biographical legal drama film about a young Thurgood Marshall, directed by Reginald Hudlin and starring Chadwick Boseman.
-
C.
Marshall
Marshall is a masculine given name of English origin commonly used in the United States and other English-speaking countries.
-
D.
Marshall
Marshall is a small unincorporated coastal community in Marin County, California, known for its oyster farms along the eastern shore of Tomales Bay.
-
E.
Marshall
Marshall is the enthusiastic Dalmatian fire-pup and medic from the PAW Patrol franchise, known for his clumsiness, big heart, and heroic rescues.
- 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: Marshall Triple: [Marshall Thundering Herd football, shortName, Marshall]
Generated description
Marshall is the college football team representing Marshall University, competing in NCAA Division I as the Thundering Herd.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marshall Target entity description: Marshall is the college football team representing Marshall University, competing in NCAA Division I as the Thundering Herd.
-
A.
Marshall
Marshall is a small East Texas city known for its historic architecture, role in the Civil War era, and cultural institutions such as Wiley College.
-
B.
Marshall
Marshall is a masculine given name of English origin commonly used in the United States and other English-speaking countries.
-
C.
Marshall
Marshall is one of the Adirondack High Peaks in New York’s Adirondack Mountains, known for its remote location and challenging, often trailless ascent.
-
D.
Marshall
Marshall is the enthusiastic Dalmatian fire-pup and medic from the PAW Patrol franchise, known for his clumsiness, big heart, and heroic rescues.
-
E.
Marshall
Marshall is a small unincorporated coastal community in Marin County, California, known for its oyster farms along the eastern shore of Tomales Bay.
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2ed48308190b9350a323b9a7952 |
completed | April 20, 2026, 11:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08c5999180819091f3f1255b490150 |
completed | May 16, 2026, 7:29 p.m. |
| NEDg | Description generation | batch_6a08c6b3abf881909c9cb0e6ec85b84f |
completed | May 16, 2026, 7:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08c778429081909235b628ba07d574 |
completed | May 16, 2026, 7:37 p.m. |
Created at: April 16, 2026, 11:43 a.m.