Triple

T21150539
Position Surface form Disambiguated ID Type / Status
Subject Xiong Xiling E521174 entity
Predicate givenName P17 FINISHED
Object Xiling
Xiling is the given name of Xiong Xiling, a prominent early 20th-century Chinese politician and philanthropist who briefly served as Premier of the Republic of China.
 E1468518 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: Xiling | Statement: [Xiong Xiling, givenName, Xiling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Xiling
Context triple: [Xiong Xiling, givenName, Xiling]
  • A. Huanglong
    Huanglong was a historical Chinese era name used during the reign of Eastern Wu ruler Sun Quan in the Three Kingdoms period.
  • B. Ximoluo
    Ximoluo is a subgroup of the Waic peoples, an ethnolinguistic cluster within the broader Tai-speaking communities of Southeast Asia.
  • C. T’eng
    T’eng is an alternative transliteration of the Chinese surname and place name commonly rendered as "Teng" in pinyin.
  • D. Erkang
    Erkang is a fictional nobleman and imperial guard commander from the popular Chinese television drama series "My Fair Princess" (Huan Zhu Ge Ge).
  • E. Yangsansi
    Yangsansi is a city in South Korea located within Gyeonggi Province, forming part of the greater Seoul metropolitan area.
  • 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: Xiling
Triple: [Xiong Xiling, givenName, Xiling]
Generated description
Xiling is the given name of Xiong Xiling, a prominent early 20th-century Chinese politician and philanthropist who briefly served as Premier of the Republic of China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Xiling
Target entity description: Xiling is the given name of Xiong Xiling, a prominent early 20th-century Chinese politician and philanthropist who briefly served as Premier of the Republic of China.
  • A. Huanglong
    Huanglong was a historical Chinese era name used during the reign of Eastern Wu ruler Sun Quan in the Three Kingdoms period.
  • B. Ximoluo
    Ximoluo is a subgroup of the Waic peoples, an ethnolinguistic cluster within the broader Tai-speaking communities of Southeast Asia.
  • C. T’eng
    T’eng is an alternative transliteration of the Chinese surname and place name commonly rendered as "Teng" in pinyin.
  • D. Erkang
    Erkang is a fictional nobleman and imperial guard commander from the popular Chinese television drama series "My Fair Princess" (Huan Zhu Ge Ge).
  • E. Yangsansi
    Yangsansi is a city in South Korea located within Gyeonggi Province, forming part of the greater Seoul metropolitan area.
  • 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_69e0b50c6a848190a4e525a77a319b8a completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72400911c8190978e88138a9bfaff completed April 21, 2026, 7:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a096dc839c88190be097464d8a641b3 completed May 17, 2026, 7:27 a.m.
NEDg Description generation batch_6a096e90901081909f96dcf0a7acb6cd completed May 17, 2026, 7:30 a.m.
NED2 Entity disambiguation (via description) batch_6a096f0ce3bc8190a5a82d718a898e13 completed May 17, 2026, 7:32 a.m.
Created at: April 16, 2026, 2:58 p.m.