Triple
T10897695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Hong |
E257352
|
entity |
| Predicate | voicedCharacter |
P2000
|
FINISHED |
| Object | Mr. Ping |
E708896
|
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: Mr. Ping | Statement: [James Hong, voicedCharacter, Mr. Ping]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Ping Context triple: [James Hong, voicedCharacter, Mr. Ping]
-
A.
Mr. Ping
chosen
Mr. Ping is Po’s adoptive goose father and a noodle shop owner in the Kung Fu Panda film series.
-
B.
Mr. Wong
Mr. Wong is the enigmatic criminal mastermind and primary antagonist in the 1934 mystery film "The Mysterious Mr. Wong."
-
C.
Madame Peng
Madame Peng is the honorific name commonly used for Peng Liyuan, a renowned Chinese soprano and the wife of Chinese leader Xi Jinping.
-
D.
Señor Chang
Señor Chang is the unhinged, often antagonistic Spanish teacher-turned-student from the TV series "Community," known for his erratic behavior and over-the-top antics.
-
E.
Shen Te
Shen Te is the central character in Bertolt Brecht’s play "The Good Person of Szechwan," a compassionate but struggling woman whose attempts to live morally in a corrupt society force her to adopt a harsher alter ego.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75d03a3fc81908df039b9b5ab9ca2 |
completed | April 9, 2026, 8:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e15524ec5c8190a330ce5fc16dd11d |
completed | April 16, 2026, 9:31 p.m. |
Created at: April 8, 2026, 9:21 p.m.