Triple
T14753722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 海河 |
E346677
|
entity |
| Predicate | sourceConfluence |
P2416
|
FINISHED |
| Object |
子牙河
子牙河是中国华北地区一条重要河流，流经河北、天津等地并最终汇入渤海。
|
E346677
|
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: 子牙河 | Statement: [海河, sourceConfluence, 子牙河]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 子牙河 Context triple: [海河, sourceConfluence, 子牙河]
-
A.
滹沱河
滹沱河是中国华北地区一条重要河流，流经山西和河北等地并最终汇入海河水系。
-
B.
海河
海河是中国北方重要的河流和水系之一，流经天津等地并最终注入渤海。
-
C.
延河
延河是中国黄土高原上一条重要支流河流，流经陕西省延安地区并最终汇入黄河。
-
D.
保津川
保津川 is a scenic river in Kyoto Prefecture, Japan, famous for its traditional boat rides through the forested ravines between Kameoka and Arashiyama.
-
E.
汾河
汾河是中国山西省境内黄河第二大支流，也是该省重要的母亲河和生态、经济发展轴线之一。
- 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: 子牙河 Triple: [海河, sourceConfluence, 子牙河]
Generated description
子牙河是中国华北地区一条重要河流，流经河北、天津等地并最终汇入渤海。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 子牙河 Target entity description: 子牙河是中国华北地区一条重要河流，流经河北、天津等地并最终汇入渤海。
-
A.
滹沱河
滹沱河是中国华北地区一条重要河流，流经山西和河北等地并最终汇入海河水系。
-
B.
海河
chosen
海河是中国北方重要的河流和水系之一，流经天津等地并最终注入渤海。
-
C.
延河
延河是中国黄土高原上一条重要支流河流，流经陕西省延安地区并最终汇入黄河。
-
D.
保津川
保津川 is a scenic river in Kyoto Prefecture, Japan, famous for its traditional boat rides through the forested ravines between Kameoka and Arashiyama.
-
E.
汾河
汾河是中国山西省境内黄河第二大支流，也是该省重要的母亲河和生态、经济发展轴线之一。
- F. None of above.
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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d59df08190a86da5048358bd6e |
completed | April 14, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb9c725881908004368772fa528d |
completed | May 8, 2026, 3:05 p.m. |
| NEDg | Description generation | batch_69fdfde8ed30819083600cdac241675e |
completed | May 8, 2026, 3:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdfe969a6081908f4ebec0f6538811 |
completed | May 8, 2026, 3:17 p.m. |
Created at: April 10, 2026, 1:30 a.m.