Triple
T15591328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teng |
E374749
|
entity |
| Predicate | hasVariantTransliteration |
P5923
|
FINISHED |
| Object |
T’eng
T’eng is an alternative transliteration of the Chinese surname and place name commonly rendered as "Teng" in pinyin.
|
E1165338
|
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: T’eng | Statement: [Teng, hasVariantTransliteration, T’eng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T’eng Context triple: [Teng, hasVariantTransliteration, T’eng]
-
A.
Tiu Keng Leng
Tiu Keng Leng is a residential area and former resettlement district in eastern Kowloon, Hong Kong, known for its high-rise housing estates and MTR interchange station.
-
B.
Daliang
Daliang was the principal city and political center of the ancient Chinese State of Wei during the Warring States period.
-
C.
Ximoluo
Ximoluo is a subgroup of the Waic peoples, an ethnolinguistic cluster within the broader Tai-speaking communities of Southeast Asia.
-
D.
Thamien
Thamien is an alternate name for the Tamyen, a Native American people and language historically associated with the San Francisco Bay Area in California.
-
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: T’eng Triple: [Teng, hasVariantTransliteration, T’eng]
Generated description
T’eng is an alternative transliteration of the Chinese surname and place name commonly rendered as "Teng" in pinyin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: T’eng Target entity description: T’eng is an alternative transliteration of the Chinese surname and place name commonly rendered as "Teng" in pinyin.
-
A.
Tiu Keng Leng
Tiu Keng Leng is a residential area and former resettlement district in eastern Kowloon, Hong Kong, known for its high-rise housing estates and MTR interchange station.
-
B.
Daliang
Daliang was the principal city and political center of the ancient Chinese State of Wei during the Warring States period.
-
C.
Ximoluo
Ximoluo is a subgroup of the Waic peoples, an ethnolinguistic cluster within the broader Tai-speaking communities of Southeast Asia.
-
D.
Thamien
Thamien is an alternate name for the Tamyen, a Native American people and language historically associated with the San Francisco Bay Area in California.
-
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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e4b903c8190a35f9267cb38e721 |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c55fa248190b114a5b63560f87b |
completed | May 9, 2026, 3:01 p.m. |
| NEDg | Description generation | batch_69ff50020d748190be36f3c08df43e40 |
completed | May 9, 2026, 3:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff50a349688190ab7a18fa4460d86e |
completed | May 9, 2026, 3:20 p.m. |
Created at: April 10, 2026, 4:11 a.m.