Triple
T2312084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peng |
E51981
|
entity |
| Predicate | hasVariantTransliteration |
P5923
|
FINISHED |
| Object | P’eng |
E51981
|
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: P’eng | Statement: [Peng, hasVariantTransliteration, P’eng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: P’eng Context triple: [Peng, hasVariantTransliteration, P’eng]
-
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.
Poh Pitu
Poh Pitu was an early capital city of the Medang Kingdom, an ancient Javanese Hindu-Buddhist polity in what is now Indonesia.
-
C.
Penge
Penge is a suburban district in southeast London known for its Victorian architecture and proximity to Crystal Palace.
-
D.
Palas
Palas is the main residential and ceremonial building within Nuremberg Castle, historically used as the living quarters and audience hall of the ruling nobility.
-
E.
Pischa
Pischa is a mountain area and ski region near Davos in the Swiss Alps, known for its freeride terrain and winter sports opportunities.
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc61a8e248190b5024cca9efd806d |
completed | March 7, 2026, 6:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae895c95388190848f592fc5d48ec6 |
completed | March 9, 2026, 8:48 a.m. |
Created at: March 4, 2026, 7:49 p.m.