Triple
T1479348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wesleyan University |
E30915
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
Wes
Wes is a common shorthand name for Wesleyan University, a private liberal arts institution known for its rigorous academics and vibrant campus culture.
|
E169026
|
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: Wes | Statement: [Wesleyan University, abbreviation, Wes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wes Context triple: [Wesleyan University, abbreviation, Wes]
-
A.
Walter
Walter is a masculine given name of Germanic origin that has been widely used in English-speaking countries.
-
B.
Neal
Neal is a masculine given name of Gaelic origin, commonly used in English-speaking countries.
-
C.
Wilkin
Wilkin is a medieval English given name that originated as a diminutive form of William and later gave rise to the surname Wilkinson.
-
D.
Willson
Willson is a less common spelling variant of the surname Wilson, typically used as a family name or occasionally as a given name.
-
E.
Wesley Saunders
Wesley Saunders is an American basketball player best known for starring as a versatile guard/forward for Harvard University, where he became one of the program’s top performers in the early 2010s.
- 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: Wes Triple: [Wesleyan University, abbreviation, Wes]
Generated description
Wes is a common shorthand name for Wesleyan University, a private liberal arts institution known for its rigorous academics and vibrant campus culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wes Target entity description: Wes is a common shorthand name for Wesleyan University, a private liberal arts institution known for its rigorous academics and vibrant campus culture.
-
A.
Walter
Walter is a masculine given name of Germanic origin that has been widely used in English-speaking countries.
-
B.
Neal
Neal is a masculine given name of Gaelic origin, commonly used in English-speaking countries.
-
C.
Wilkin
Wilkin is a medieval English given name that originated as a diminutive form of William and later gave rise to the surname Wilkinson.
-
D.
Willson
Willson is a less common spelling variant of the surname Wilson, typically used as a family name or occasionally as a given name.
-
E.
Wesley Saunders
Wesley Saunders is an American basketball player best known for starring as a versatile guard/forward for Harvard University, where he became one of the program’s top performers in the early 2010s.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c6739d2481909ea8d8e075f62cf3 |
completed | March 1, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad15aff1288190a3e36324d975d482 |
completed | March 8, 2026, 6:22 a.m. |
| NEDg | Description generation | batch_69ad1639e21081908737b51e910ceae3 |
completed | March 8, 2026, 6:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad16a98fd08190a14f4d7d6b11f5e8 |
completed | March 8, 2026, 6:26 a.m. |
Created at: March 1, 2026, 8:11 p.m.