Triple
T19580711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northeast China rail network |
E489979
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Tonghua |
E536849
|
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: Tonghua | Statement: [Northeast China rail network, connects, Tonghua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tonghua Context triple: [Northeast China rail network, connects, Tonghua]
-
A.
Tonghua
chosen
Tonghua is a prefecture-level city in southeastern Jilin Province, China, known for its mountainous terrain, pharmaceutical industry, and role as a regional transportation hub.
-
B.
Zhizhong
Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
-
C.
Yifang
Yifang is a given name of Chinese origin used for both males and females.
-
D.
Taohuayuan
Taohuayuan is a famous scenic area and cultural site in Changde, Hunan, inspired by the classic Chinese utopian tale "Peach Blossom Spring."
-
E.
Xinzhu
Xinzhu is a city that serves as a sister city to Bielefeld, Germany, and is likely a regional urban center with cultural and economic significance.
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e640281b7c8190be44268a58df058f |
completed | April 20, 2026, 3:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0771a73b5c81908ccd177a00b4ca05 |
completed | May 15, 2026, 7:19 p.m. |
Created at: April 10, 2026, 1:42 p.m.