Triple
T13684749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gubeikou |
E328092
|
entity |
| Predicate | nearbySection |
P61270
|
FINISHED |
| Object | Simatai |
E1044535
|
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: Simatai | Statement: [Gubeikou, nearbySection, Simatai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Simatai Context triple: [Gubeikou, nearbySection, Simatai]
-
A.
Simatai
chosen
Simatai is a steep, well-preserved, and scenic section of the Great Wall of China located in the mountains northeast of Beijing.
-
B.
Pai Mei
Pai Mei is a legendary, ruthless martial arts master in Quentin Tarantino’s Kill Bill saga, known for his brutal training methods and near-mythic fighting skills.
-
C.
Taihu Wu
Taihu Wu is a major subgroup of the Wu varieties of Chinese, spoken in and around the Yangtze River Delta including cities such as Shanghai, Suzhou, and Hangzhou.
-
D.
Kook-Chun
Kook-Chun is the family name of actor Shannon Kook, known for his roles in film and television.
-
E.
Wai Lin
Wai Lin is a highly skilled Chinese secret agent and martial artist who partners with James Bond in the film "Tomorrow Never Dies."
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8746458819095ec1ba3c01ef31b |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7944765488190a97d2bea8c29e698 |
completed | May 3, 2026, 6:30 p.m. |
Created at: April 9, 2026, 9:53 p.m.