Triple
T10110501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject |
E218225
|
entity | |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | WeChat Mini Programs |
E218225
|
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: WeChat Mini Programs | Statement: [WeChat, hasComponent, WeChat Mini Programs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WeChat Mini Programs Context triple: [WeChat, hasComponent, WeChat Mini Programs]
-
A.
WeChat
chosen
WeChat is a Chinese multi-purpose mobile app developed by Tencent that combines messaging, social media, and payment services into a single platform.
-
B.
Xigua Video
Xigua Video is a Chinese online video-sharing and streaming platform owned by ByteDance, offering a mix of user-generated and professionally produced content.
-
C.
DingTalk
DingTalk is a Chinese enterprise communication and collaboration platform that offers messaging, video conferencing, task management, and office automation tools for businesses.
-
D.
Xiaoju Technology
Xiaoju Technology is the former corporate name of Didi Chuxing, the Chinese ride-hailing and mobility technology company.
-
E.
Opera Mini
Opera Mini is a lightweight mobile web browser designed to compress data and load pages quickly, especially on slower networks and lower-end devices.
- 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0cf39908190bba679ace095eefc |
completed | April 2, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cc1805d08190bc39aadf1e84a569 |
completed | April 5, 2026, 8:54 p.m. |
Created at: March 30, 2026, 9:03 p.m.