Triple
T27847198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Good Lawyer’s Wife |
E703855
|
entity |
| Predicate | releaseDateInSouthKorea |
P33095
|
FINISHED |
| Object | 2003-08-15 |
—
|
LITERAL FINISHED |
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: 2003-08-15 | Statement: [A Good Lawyer’s Wife, releaseDateInSouthKorea, 2003-08-15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: releaseDateInSouthKorea Context triple: [A Good Lawyer’s Wife, releaseDateInSouthKorea, 2003-08-15]
-
A.
releaseDateSouthKorea
chosen
Indicates the date on which something (such as a product, film, or work) was officially released in South Korea.
-
B.
releaseDateAsia
Indicates the date on which something is officially released or made available in Asian markets.
-
C.
releaseDateJapan
Indicates the date on which something is officially released or made available in Japan.
-
D.
releaseDateTaiwan
Indicates the date on which something (such as a product, film, or media) was officially released in Taiwan.
-
E.
releaseDateInHongKong
Indicates the date on which something is officially released or made available in Hong Kong.
- F. None of above.
Provenance (3 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_69ef840d9e3c819093615ebff4ec22be |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 27, 2026, 6:08 p.m.