Triple
T21088125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jerome Sacks |
E519556
|
entity |
| Predicate | hasNotableStudent |
P4838
|
FINISHED |
| Object |
C. F. Jeff Wu
C. F. Jeff Wu is a prominent statistician known for his influential work in industrial statistics, quality engineering, and the popularization of the term "data science."
|
E1466543
|
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: C. F. Jeff Wu | Statement: [Jerome Sacks, hasNotableStudent, C. F. Jeff Wu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: C. F. Jeff Wu Context triple: [Jerome Sacks, hasNotableStudent, C. F. Jeff Wu]
-
A.
Chi-lung Shih
Chi-lung Shih is the Wade–Giles romanization of Keelung City, a major port city in northern Taiwan.
-
B.
Fu-Sheng Chiu
Fu-Sheng Chiu is a film producer best known for his work on acclaimed Chinese-language cinema, including the internationally recognized drama "To Live."
-
C.
Kuo-Chen Huang
Kuo-Chen Huang was a physicist whose work on electron–phonon coupling in solids led to the formulation of the Huang–Rhys factor in solid-state spectroscopy.
-
D.
Pao-Chi Chang
Pao-Chi Chang is a cinematographer best known for his work on the action-comedy film "Shanghai Noon."
-
E.
Chih-Chung Chang
Chih-Chung Chang is a computer scientist best known as a primary developer of the widely used LIBSVM library for support vector machines.
- 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: C. F. Jeff Wu Triple: [Jerome Sacks, hasNotableStudent, C. F. Jeff Wu]
Generated description
C. F. Jeff Wu is a prominent statistician known for his influential work in industrial statistics, quality engineering, and the popularization of the term "data science."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: C. F. Jeff Wu Target entity description: C. F. Jeff Wu is a prominent statistician known for his influential work in industrial statistics, quality engineering, and the popularization of the term "data science."
-
A.
Chi-lung Shih
Chi-lung Shih is the Wade–Giles romanization of Keelung City, a major port city in northern Taiwan.
-
B.
Fu-Sheng Chiu
Fu-Sheng Chiu is a film producer best known for his work on acclaimed Chinese-language cinema, including the internationally recognized drama "To Live."
-
C.
Kuo-Chen Huang
Kuo-Chen Huang was a physicist whose work on electron–phonon coupling in solids led to the formulation of the Huang–Rhys factor in solid-state spectroscopy.
-
D.
Pao-Chi Chang
Pao-Chi Chang is a cinematographer best known for his work on the action-comedy film "Shanghai Noon."
-
E.
Chih-Chung Chang
Chih-Chung Chang is a computer scientist best known as a primary developer of the widely used LIBSVM library for support vector machines.
- 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_69e0b507dd9081908fb8bfcbef4c8b46 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7094cebe08190bb10f51a45c244ec |
completed | April 21, 2026, 5:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a095a560a508190b4e69a73e6302836 |
completed | May 17, 2026, 6:04 a.m. |
| NEDg | Description generation | batch_6a095c58689481909fb5ab261870e7e6 |
completed | May 17, 2026, 6:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a095d21b59881909898c9581fc21ba7 |
completed | May 17, 2026, 6:16 a.m. |
Created at: April 16, 2026, 2:50 p.m.