Triple
T352758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MIT Stata Center |
E7477
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Maria Stata
Maria Stata is the namesake of MIT’s Stata Center, recognized for her association with and philanthropic support of the Massachusetts Institute of Technology.
|
E44620
|
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: Maria Stata | Statement: [MIT Stata Center, namedAfter, Maria Stata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Stata Context triple: [MIT Stata Center, namedAfter, Maria Stata]
-
A.
Leia Maria Nadler
Leia Maria Nadler is the wife of former United Nations Secretary-General Boutros Boutros-Ghali.
-
B.
Elizabeth Pomada
Elizabeth Pomada is an American author and historian best known for popularizing San Francisco’s colorful Victorian houses through her influential work on the “Painted Ladies.”
-
C.
Jane Belson
Jane Belson was a British barrister best known as the wife of author Douglas Adams.
-
D.
Kathleen
Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
-
E.
Mary Quinn Sullivan
Mary Quinn Sullivan was an American art collector and patron who played a key role in the early promotion and institutional support of modern art in the United States.
- 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: Maria Stata Triple: [MIT Stata Center, namedAfter, Maria Stata]
Generated description
Maria Stata is the namesake of MIT’s Stata Center, recognized for her association with and philanthropic support of the Massachusetts Institute of Technology.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maria Stata Target entity description: Maria Stata is the namesake of MIT’s Stata Center, recognized for her association with and philanthropic support of the Massachusetts Institute of Technology.
-
A.
Leia Maria Nadler
Leia Maria Nadler is the wife of former United Nations Secretary-General Boutros Boutros-Ghali.
-
B.
Elizabeth Pomada
Elizabeth Pomada is an American author and historian best known for popularizing San Francisco’s colorful Victorian houses through her influential work on the “Painted Ladies.”
-
C.
Jane Belson
Jane Belson was a British barrister best known as the wife of author Douglas Adams.
-
D.
Kathleen
Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
-
E.
Mary Quinn Sullivan
Mary Quinn Sullivan was an American art collector and patron who played a key role in the early promotion and institutional support of modern art in the United States.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb7f1be88190964ddcbb6a05f021 |
completed | Feb. 28, 2026, 1:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3dd353b488190b6ed966290260806 |
completed | March 1, 2026, 6:31 a.m. |
| NEDg | Description generation | batch_69a3ddbbe7e08190ac167e158d19dbce |
completed | March 1, 2026, 6:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3de3fef7c819082193eb7083175e1 |
completed | March 1, 2026, 6:35 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.