Triple
T689186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anhui |
E13352
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Ma’anshan
Ma’anshan is an industrial city in eastern China known for its steel production and location along the lower Yangtze River.
|
E95967
|
NE FINISHED |
How this triple was built (4 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: Ma’anshan | Statement: [Anhui, containsCity, Ma’anshan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ma’anshan Context triple: [Anhui, containsCity, Ma’anshan]
-
A.
Huangshi
Huangshi is an industrial city in eastern Hubei Province, China, known for its steel production and location along the Yangtze River.
-
B.
Xiantao
Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
-
C.
Jingmen
Jingmen is a prefecture-level city in central China known for its role as a regional industrial and transportation hub within Hubei Province.
-
D.
Anyang
Anyang is an ancient city in northern China renowned as one of the historical capitals of the Shang dynasty and a major archaeological site.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ma’anshan Triple: [Anhui, containsCity, Ma’anshan]
Generated description
Ma’anshan is an industrial city in eastern China known for its steel production and location along the lower Yangtze River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ma’anshan Target entity description: Ma’anshan is an industrial city in eastern China known for its steel production and location along the lower Yangtze River.
-
A.
Huangshi
Huangshi is an industrial city in eastern Hubei Province, China, known for its steel production and location along the Yangtze River.
-
B.
Xiantao
Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
-
C.
Jingmen
Jingmen is a prefecture-level city in central China known for its role as a regional industrial and transportation hub within Hubei Province.
-
D.
Anyang
Anyang is an ancient city in northern China renowned as one of the historical capitals of the Shang dynasty and a major archaeological site.
-
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. chosen
Provenance (5 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a09669e4819089753204772e1fdd |
completed | March 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d6ed1f881909fea81ce4308075b |
completed | March 3, 2026, 11:23 p.m. |
| NEDg | Description generation | batch_69a771ec72a88190a62539ca5ed3a94d |
completed | March 3, 2026, 11:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7723dcf488190968a64f68fce9c63 |
completed | March 3, 2026, 11:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.