Triple
T19328768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gie-Ming Lin |
E483429
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Gie-Ming Lin |
—
|
NE NERFINISHED |
How this triple was built (2 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: Gie-Ming Lin | Statement: [Gie-Ming Lin, name, Gie-Ming Lin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gie-Ming Lin Context triple: [Gie-Ming Lin, name, Gie-Ming Lin]
-
A.
Gie-Ming Lin
chosen
Gie-Ming Lin is known primarily as a family member of Shirley Lin, likely recognized in relation to her public or professional profile.
-
B.
Tung-Yen Lin
Tung-Yen Lin was a pioneering Chinese-American structural engineer renowned for his groundbreaking work in prestressed concrete and major bridge designs worldwide.
-
C.
Cho-Liang Lin
Cho-Liang Lin is a Taiwanese-American violinist renowned for his virtuosity, lyrical tone, and international solo career, including acclaimed performances with major orchestras and extensive recordings.
-
D.
Wei-Ning Hsu
Wei-Ning Hsu is a researcher in speech and audio processing, known for co-developing the HuBERT self-supervised learning model for speech representation.
-
E.
Chi-lung Shih
Chi-lung Shih is the Wade–Giles romanization of Keelung City, a major port city in northern Taiwan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6163ffddc81909e9cb13e780f1f18 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 10, 2026, 1:33 p.m.