Triple
T19092322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eddie Peng |
E467317
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Peng |
—
|
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: Peng | Statement: [Eddie Peng, familyName, Peng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peng Context triple: [Eddie Peng, familyName, Peng]
-
A.
Peng
chosen
Peng is a Chinese surname borne by numerous notable figures in politics, arts, and academia throughout Chinese history and the modern era.
-
B.
Pengim
Pengim is a romanization system used to represent the sounds of the Teochew (Chaozhou) Chinese dialect with the Latin alphabet.
-
C.
Peng-Peng
Peng-Peng is the nickname of Peng-Peng Lee, a Canadian-American artistic gymnast known for her elite career and standout NCAA performances with UCLA.
-
D.
Penge
Penge is a suburban district in southeast London known for its Victorian architecture and proximity to Crystal Palace.
-
E.
Pang
Pang is a variant transliteration of the Chinese surname commonly romanized as Peng.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e34c22a08190bf34f92f727268c5 |
completed | April 20, 2026, 8:26 a.m. |
Created at: April 10, 2026, 12:04 p.m.