Triple
T5264444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hwang Jun-ho |
E118904
|
entity |
| Predicate | enemyOf |
P437
|
FINISHED |
| Object | Front Man |
E485599
|
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: Front Man | Statement: [Hwang Jun-ho, enemyOf, Front Man]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Front Man Context triple: [Hwang Jun-ho, enemyOf, Front Man]
-
A.
Front Man
chosen
Front Man is the masked overseer and main antagonist who secretly runs the deadly survival games in the South Korean series "Squid Game."
-
B.
Mr. Man
"Mr. Man" is a song by Alicia Keys from her debut studio album "Songs in A Minor."
-
C.
Don Front
Don Front was a major Soviet military formation on the Eastern Front of World War II, instrumental in the encirclement and defeat of German forces at Stalingrad.
-
D.
Handsome Dan
Handsome Dan is the live bulldog mascot and enduring symbol of Yale University's athletic teams and school spirit.
-
E.
Roker
Roker is a coastal suburb of Sunderland in North East England, known for its sandy beach, seafront promenade, and historic lighthouse.
- 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bd4a9888190a79ef8e64c764f86 |
completed | March 20, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf06c71d308190a42a2da51b4cf93e |
completed | March 21, 2026, 8:59 p.m. |
Created at: March 20, 2026, 1:51 p.m.