Triple
T14124370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lüliang |
E339988
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Linfen |
E335875
|
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: Linfen | Statement: [Lüliang, borders, Linfen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linfen Context triple: [Lüliang, borders, Linfen]
-
A.
Linfen
chosen
Linfen is a major industrial city in southern Shanxi Province, China, historically known for coal production and severe air pollution.
-
B.
Jincheng
Jincheng is an ancient name historically used for the Chinese city now known as Lanzhou, a key regional center along the Silk Road in Gansu Province.
-
C.
Jincheng
Jincheng is the main urban township and administrative center of Kinmen County, located on the outlying Kinmen Islands governed by Taiwan.
-
D.
Jincheng
Jincheng is a prefecture-level city in southeastern Shanxi Province, China, known for its coal resources and heavy industry.
-
E.
Weinan
Weinan is a prefecture-level city in eastern Shaanxi Province, China, known for its historical sites and location near the Wei River.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6096976481909dc79066c5165a50 |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd19356478819083406440c22c38e2 |
completed | May 7, 2026, 10:59 p.m. |
Created at: April 9, 2026, 10:22 p.m.