Triple
T21748533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tonghua |
E536849
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Siping |
—
|
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: Siping | Statement: [Tonghua, borders, Siping]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siping Context triple: [Tonghua, borders, Siping]
-
A.
Siping
Siping is a prefecture-level city in northeastern China known for its agricultural base and strategic location within Jilin Province.
-
B.
Siping City
chosen
Siping City is a prefecture-level city in southwestern Jilin Province, northeastern China, known as a regional hub for agriculture and industry.
-
C.
Helong
The Helong are an indigenous ethnic group of western Timor known for their distinct Austronesian language and traditional coastal and island communities.
-
D.
Helong
Helong is a county-level city in northeastern China's Jilin Province, known for its significant ethnic Korean population and role within the Yanbian Korean Autonomous Prefecture.
-
E.
Baishan
Baishan is a prefecture-level city in southeastern Jilin Province, China, known for its mountainous terrain, forest resources, and proximity to Changbai Mountain.
- 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a77e19c81909bf26f96aa41a7ce |
completed | April 28, 2026, 2:24 a.m. |
Created at: April 16, 2026, 6:50 p.m.