Triple
T14916831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanking Road |
E371402
|
entity |
| Predicate | hasMajorIntersection |
P12328
|
FINISHED |
| Object |
Xizang Road
Xizang Road is a major north–south thoroughfare in central Shanghai, China, known for intersecting key commercial streets and serving as an important urban traffic artery.
|
E1129582
|
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: Xizang Road | Statement: [Nanking Road, hasMajorIntersection, Xizang Road]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xizang Road Context triple: [Nanking Road, hasMajorIntersection, Xizang Road]
-
A.
South Xizang Road
South Xizang Road is a metro station in Shanghai that serves as part of the city's urban rapid transit network.
-
B.
Tianshan Road
Tianshan Road is a major commercial and residential street in Shanghai, China, known for its shops, offices, and urban amenities.
-
C.
Hailun Road
Hailun Road is a Shanghai Metro interchange station located in Hongkou District, serving as a stop on multiple urban rail lines.
-
D.
Lancun Road
Lancun Road is a Shanghai Metro interchange station serving multiple lines in the Pudong New Area of Shanghai, China.
-
E.
Yishan Road
Yishan Road is a Shanghai Metro interchange station serving multiple lines in the Xuhui District of Shanghai, China.
- 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: Xizang Road Triple: [Nanking Road, hasMajorIntersection, Xizang Road]
Generated description
Xizang Road is a major north–south thoroughfare in central Shanghai, China, known for intersecting key commercial streets and serving as an important urban traffic artery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xizang Road Target entity description: Xizang Road is a major north–south thoroughfare in central Shanghai, China, known for intersecting key commercial streets and serving as an important urban traffic artery.
-
A.
South Xizang Road
South Xizang Road is a metro station in Shanghai that serves as part of the city's urban rapid transit network.
-
B.
Tianshan Road
Tianshan Road is a major commercial and residential street in Shanghai, China, known for its shops, offices, and urban amenities.
-
C.
Hailun Road
Hailun Road is a Shanghai Metro interchange station located in Hongkou District, serving as a stop on multiple urban rail lines.
-
D.
Lancun Road
Lancun Road is a Shanghai Metro interchange station serving multiple lines in the Pudong New Area of Shanghai, China.
-
E.
Yishan Road
Yishan Road is a Shanghai Metro interchange station serving multiple lines in the Xuhui District of Shanghai, China.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded62038508190946499cd3552990e |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bd1a4548190a14e246ab69ed21c |
completed | May 9, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_69fe8f1a6984819088ff8c47beb0579c |
completed | May 9, 2026, 1:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe8f4c9b7c8190bbc6fa76ee7f00bc |
completed | May 9, 2026, 1:35 a.m. |
Created at: April 10, 2026, 2:32 a.m.