Triple
T13872270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woo |
E333483
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Goh |
E333484
|
NE 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: Goh | Statement: [Woo, hasVariantSpelling, Goh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goh Context triple: [Woo, hasVariantSpelling, Goh]
-
A.
Goh
chosen
Goh is a surname and given name commonly found in East and Southeast Asia, often representing a romanization of several different Chinese surnames.
-
B.
Gooigi
Gooigi is a green, goo-like doppelgänger of Luigi from the Luigi’s Mansion series, used as a playable helper character to solve puzzles and reach otherwise inaccessible areas.
-
C.
Kogo
Kogo is a settlement located in the Litoral region of Equatorial Guinea.
-
D.
Goh Kun
Goh Kun is a South Korean politician and bureaucrat who served as Prime Minister and held multiple key administrative posts, including leadership roles in Seoul's municipal government.
-
E.
Mogis
Mogis is the surname of Mike Mogis, an American musician and record producer best known for his work with the indie rock band Bright Eyes and the Saddle Creek Records scene.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de05c638248190bbe5d19f7b88d0f9 |
completed | April 14, 2026, 9:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c107c20c81909dff0ca4a59fcc55 |
completed | May 3, 2026, 9:41 p.m. |
Created at: April 9, 2026, 10:14 p.m.