Triple
T12590937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haifan Lin |
E300600
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object |
Yukiko Yamashita
Yukiko Yamashita is a developmental biologist known for her research on stem cell biology and asymmetric cell division.
|
E1010647
|
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: Yukiko Yamashita | Statement: [Haifan Lin, notableStudent, Yukiko Yamashita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yukiko Yamashita Context triple: [Haifan Lin, notableStudent, Yukiko Yamashita]
-
A.
Akiko Yoshida
Akiko Yoshida is an individual known primarily through her close personal association with Steve Smith.
-
B.
Akiko Yoshida
Akiko Yoshida is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
-
C.
Yūko Kishi
Yūko Kishi is a Japanese individual notable enough to be recognized as a prominent bearer of the surname Kishi.
-
D.
Makiko Tanaka
Makiko Tanaka is a Japanese politician and former foreign minister, known as the outspoken daughter of influential former Prime Minister Kakuei Tanaka.
-
E.
Yoshiko Satō
Yoshiko Satō is a Japanese individual notable enough to be recognized as a prominent bearer of the surname Satō.
- 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: Yukiko Yamashita Triple: [Haifan Lin, notableStudent, Yukiko Yamashita]
Generated description
Yukiko Yamashita is a developmental biologist known for her research on stem cell biology and asymmetric cell division.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yukiko Yamashita Target entity description: Yukiko Yamashita is a developmental biologist known for her research on stem cell biology and asymmetric cell division.
-
A.
Akiko Yoshida
Akiko Yoshida is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
-
B.
Akiko Yoshida
Akiko Yoshida is an individual known primarily through her close personal association with Steve Smith.
-
C.
Yūko Kishi
Yūko Kishi is a Japanese individual notable enough to be recognized as a prominent bearer of the surname Kishi.
-
D.
Makiko Tanaka
Makiko Tanaka is a Japanese politician and former foreign minister, known as the outspoken daughter of influential former Prime Minister Kakuei Tanaka.
-
E.
Yoshiko Satō
Yoshiko Satō is a Japanese individual notable enough to be recognized as a prominent bearer of the surname Satō.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954cc6d3c81908fbb22601c46f3f7 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af45ea888190a4b2d0c1730a06ef |
completed | May 3, 2026, 2:13 a.m. |
| NEDg | Description generation | batch_69f6b0653ef88190ad0e3a48675ecdcc |
completed | May 3, 2026, 2:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6b1ae645c8190a7c3e5f926c6a487 |
completed | May 3, 2026, 2:23 a.m. |
Created at: April 9, 2026, 5:07 p.m.