Triple
T12338113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lost and Love |
E294143
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Peng Sanyuan |
E294143
|
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: Peng Sanyuan | Statement: [Lost and Love, screenwriter, Peng Sanyuan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peng Sanyuan Context triple: [Lost and Love, screenwriter, Peng Sanyuan]
-
A.
Peng Sanyuan
chosen
Peng Sanyuan is a Chinese film and television director and screenwriter best known for socially conscious dramas such as the film "Lost and Love."
-
B.
Peng Yuchang
Peng Yuchang is a Chinese actor and singer known for his roles in popular youth films and television dramas.
-
C.
Peng Xiaolian
Peng Xiaolian was a prominent Chinese film director and screenwriter known for her nuanced portrayals of women's lives and Shanghai's urban culture.
-
D.
Peng Shige
Peng Shige is a prominent Chinese mathematician renowned for his foundational contributions to stochastic analysis and backward stochastic differential equations.
-
E.
Zhang Zongyu
Zhang Zongyu was a prominent Chinese rebel commander who led the Nian forces against the Qing dynasty during the mid-19th century.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f678698819091462b44ff3435f6 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbae345881908b2fa0a6900f601e |
completed | May 3, 2026, 4:14 a.m. |
Created at: April 8, 2026, 9:53 p.m.