Triple
T2864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Pennsylvania |
E53
|
entity |
| Predicate | hasMascot |
P52
|
FINISHED |
| Object |
The Quaker
The Quaker is the traditional, colonial-era–styled mascot representing the University of Pennsylvania and its athletic teams.
|
E199
|
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: The Quaker | Statement: [University of Pennsylvania, hasMascot, The Quaker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Quaker Context triple: [University of Pennsylvania, hasMascot, The Quaker]
-
A.
Mens et Manus
Mens et Manus is the Latin motto of the Massachusetts Institute of Technology, expressing the union of mind and hand in the pursuit of knowledge and practical application.
-
B.
Veritas
Veritas is the Latin word for "truth" and is famously used as the motto of Harvard University.
-
C.
Douglas
Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
-
D.
Theodor
Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
-
E.
Sally Kornbluth
Sally Kornbluth is an American cell biologist and academic leader who became the 18th president of the Massachusetts Institute of Technology.
- 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: The Quaker Triple: [University of Pennsylvania, hasMascot, The Quaker]
Generated description
The Quaker is the traditional, colonial-era–styled mascot representing the University of Pennsylvania and its athletic teams.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: The Quaker Target entity description: The Quaker is the traditional, colonial-era–styled mascot representing the University of Pennsylvania and its athletic teams.
-
A.
Mens et Manus
Mens et Manus is the Latin motto of the Massachusetts Institute of Technology, expressing the union of mind and hand in the pursuit of knowledge and practical application.
-
B.
Veritas
Veritas is the Latin word for "truth" and is famously used as the motto of Harvard University.
-
C.
Douglas
Douglas is a masculine given name of Scottish origin that has been widely used in English-speaking countries.
-
D.
Theodor
Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
-
E.
Sally Kornbluth
Sally Kornbluth is an American cell biologist and academic leader who became the 18th president of the Massachusetts Institute of Technology.
- 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_69a22e0d37588190897cf37a323013f5 |
completed | Feb. 27, 2026, 11:51 p.m. |
| NER | Named-entity recognition | batch_69a230c560548190a57df2421e233775 |
completed | Feb. 28, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a238e23e0881909815d2dad067d7a1 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NEDg | Description generation | batch_69a23ab3a1f481908407d4648bbf3f86 |
completed | Feb. 28, 2026, 12:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a23b736e388190956fa92a68d25866 |
completed | Feb. 28, 2026, 12:48 a.m. |
Created at: Feb. 27, 2026, 11:55 p.m.