Triple

T1976708
Position Surface form Disambiguated ID Type / Status
Subject Alibaba Group E42930 entity
Predicate tradedAs P2822 FINISHED
Object SEHK:9988
SEHK:9988 is the stock ticker for Alibaba Group’s shares listed on the Hong Kong Stock Exchange, representing one of China’s largest e-commerce and technology conglomerates.
 E223490 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: SEHK:9988 | Statement: [Alibaba Group, tradedAs, SEHK:9988]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SEHK:9988
Context triple: [Alibaba Group, tradedAs, SEHK:9988]
  • A. HKJK
    HKJK is the ICAO airport code for Jomo Kenyatta International Airport, the main international gateway serving Nairobi, Kenya.
  • B. HK
    HK is a renowned German defense manufacturer best known for designing and producing small arms such as pistols, rifles, and submachine guns used by military and law enforcement worldwide.
  • C. HK
    HK is the vehicle registration code used for the Czech city of Hradec Králové.
  • D. HK
    HK is the vehicle registration code used on license plates for vehicles registered in Ahlden, a municipality in Lower Saxony, Germany.
  • E. Kowloon
    Kowloon is a densely populated urban area of Hong Kong known for its vibrant street life, markets, and skyline facing Victoria Harbour.
  • 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: SEHK:9988
Triple: [Alibaba Group, tradedAs, SEHK:9988]
Generated description
SEHK:9988 is the stock ticker for Alibaba Group’s shares listed on the Hong Kong Stock Exchange, representing one of China’s largest e-commerce and technology conglomerates.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SEHK:9988
Target entity description: SEHK:9988 is the stock ticker for Alibaba Group’s shares listed on the Hong Kong Stock Exchange, representing one of China’s largest e-commerce and technology conglomerates.
  • A. HKJK
    HKJK is the ICAO airport code for Jomo Kenyatta International Airport, the main international gateway serving Nairobi, Kenya.
  • B. HK
    HK is a renowned German defense manufacturer best known for designing and producing small arms such as pistols, rifles, and submachine guns used by military and law enforcement worldwide.
  • C. HK
    HK is the vehicle registration code used for the Czech city of Hradec Králové.
  • D. HK
    HK is the vehicle registration code used on license plates for vehicles registered in Ahlden, a municipality in Lower Saxony, Germany.
  • E. Kowloon
    Kowloon is a densely populated urban area of Hong Kong known for its vibrant street life, markets, and skyline facing Victoria Harbour.
  • 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_69a8871289048190b00b0d7744b7b2b1 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3f9a87c8190816db3888787ad76 completed March 7, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0327600c8190adb057b596a84bca completed March 8, 2026, 11:15 p.m.
NEDg Description generation batch_69ae03b41dcc81909b4439006bdffc64 completed March 8, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_69ae0445a9608190918a7bd45b9bf999 completed March 8, 2026, 11:20 p.m.
Created at: March 4, 2026, 7:36 p.m.