Triple
T616370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taipei |
E14412
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Ximending
Ximending is a bustling shopping and entertainment district in Taipei known for its youth culture, street performances, and vibrant nightlife.
|
E77114
|
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: Ximending | Statement: [Taipei, hasLandmark, Ximending]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ximending Context triple: [Taipei, hasLandmark, Ximending]
-
A.
Xintiandi
Xintiandi is a fashionable, pedestrian-only district in central Shanghai known for its upscale shopping, dining, nightlife, and preserved Shikumen-style architecture.
-
B.
Xing
Xing is a German-based professional networking platform focused on career development and business connections, particularly in German-speaking countries.
-
C.
Shinsekai
Shinsekai is a retro entertainment district in Osaka, Japan, known for its nostalgic Showa-era atmosphere, street food, and neon-lit nightlife.
-
D.
Xuan
Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
-
E.
Kaiyukan
Kaiyukan is a large, world-renowned public aquarium in Osaka, Japan, famous for its massive central tank and immersive marine life exhibits.
- 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: Ximending Triple: [Taipei, hasLandmark, Ximending]
Generated description
Ximending is a bustling shopping and entertainment district in Taipei known for its youth culture, street performances, and vibrant nightlife.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ximending Target entity description: Ximending is a bustling shopping and entertainment district in Taipei known for its youth culture, street performances, and vibrant nightlife.
-
A.
Xintiandi
Xintiandi is a fashionable, pedestrian-only district in central Shanghai known for its upscale shopping, dining, nightlife, and preserved Shikumen-style architecture.
-
B.
Xing
Xing is a German-based professional networking platform focused on career development and business connections, particularly in German-speaking countries.
-
C.
Shinsekai
Shinsekai is a retro entertainment district in Osaka, Japan, known for its nostalgic Showa-era atmosphere, street food, and neon-lit nightlife.
-
D.
Xuan
Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
-
E.
Kaiyukan
Kaiyukan is a large, world-renowned public aquarium in Osaka, Japan, famous for its massive central tank and immersive marine life exhibits.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e22f3688190a512bec3f0347814 |
completed | March 1, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5554b4f888190b9b64ece37087bf4 |
completed | March 2, 2026, 9:15 a.m. |
| NEDg | Description generation | batch_69a555ae08b88190aad64ec7923437ef |
completed | March 2, 2026, 9:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a556669878819098816d2221a3fd3d |
completed | March 2, 2026, 9:20 a.m. |
Created at: March 1, 2026, 7:35 p.m.