Triple
T1654859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inner Mongolia Autonomous Region |
E35774
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Baotou |
E171888
|
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: Baotou | Statement: [Inner Mongolia Autonomous Region, contains, Baotou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baotou Context triple: [Inner Mongolia Autonomous Region, contains, Baotou]
-
A.
Baotou
chosen
Baotou is a major industrial city in Inner Mongolia, China, known especially for its steel production and nearby rare earth mineral processing.
-
B.
Hohhot
Hohhot is the capital and largest city of Inner Mongolia in northern China, known as a regional center of politics, culture, and industry.
-
C.
Baoding
Baoding is a historic prefecture-level city in central Hebei Province, China, known as a regional transportation hub and former military and administrative center.
-
D.
Bozhou
Bozhou is a historic city in northern Anhui Province, China, known as a major center of traditional Chinese medicine and ancient culture.
-
E.
Anshan
Anshan was an ancient city and region in southwestern Iran that served as an early center of Elamite and later Achaemenid Persian power.
- 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a8b597c81908a62b41718d85df6 |
completed | March 5, 2026, 4:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad798680088190a24dd968aab1baf0 |
completed | March 8, 2026, 1:28 p.m. |
Created at: March 4, 2026, 7:29 p.m.