Triple
T9509079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebanon Valley College |
E229343
|
entity |
| Predicate | hasMascot |
P52
|
FINISHED |
| Object |
Dutchmen
The Dutchmen are the athletic teams and mascot identity representing Lebanon Valley College in collegiate sports.
|
E804240
|
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: Dutchmen | Statement: [Lebanon Valley College, hasMascot, Dutchmen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dutchmen Context triple: [Lebanon Valley College, hasMascot, Dutchmen]
-
A.
Dutchmen
The Dutchmen is the nickname for the athletic teams representing Union College in collegiate sports.
-
B.
Dutchmen
Dutchmen is the nickname and mascot representing the athletic teams of Hope College in Holland, Michigan.
-
C.
Mackmen
The Mackmen was a nickname for the early 20th-century Philadelphia Athletics baseball team, derived from their legendary manager Connie Mack.
-
D.
Fulks
Fulks is a surname most notably associated with early professional basketball star Joe Fulks, a pioneering scorer in the Basketball Association of America.
-
E.
Udelar
Udelar is Uruguay’s main public university, renowned for its central role in the country’s higher education, research, and cultural life.
- 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: Dutchmen Triple: [Lebanon Valley College, hasMascot, Dutchmen]
Generated description
The Dutchmen are the athletic teams and mascot identity representing Lebanon Valley College in collegiate sports.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dutchmen Target entity description: The Dutchmen are the athletic teams and mascot identity representing Lebanon Valley College in collegiate sports.
-
A.
Dutchmen
Dutchmen is the nickname and mascot representing the athletic teams of Hope College in Holland, Michigan.
-
B.
Dutchmen
The Dutchmen is the nickname for the athletic teams representing Union College in collegiate sports.
-
C.
Mackmen
The Mackmen was a nickname for the early 20th-century Philadelphia Athletics baseball team, derived from their legendary manager Connie Mack.
-
D.
Fulks
Fulks is a surname most notably associated with early professional basketball star Joe Fulks, a pioneering scorer in the Basketball Association of America.
-
E.
Udelar
Udelar is Uruguay’s main public university, renowned for its central role in the country’s higher education, research, and cultural life.
- 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9857058881909e0a40e2024a7b4c |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a2b34948190826b1f58258a4f54 |
completed | April 4, 2026, 4:19 p.m. |
| NEDg | Description generation | batch_69d13bc8ce4081909a58db4014f2748d |
completed | April 4, 2026, 4:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d13c58beb08190ab41485bc7dd9b6d |
completed | April 4, 2026, 4:29 p.m. |
Created at: March 30, 2026, 7:58 p.m.