Triple

T22720344
Position Surface form Disambiguated ID Type / Status
Subject Guan peoples E561841 entity
Predicate ethnolinguisticGroup P3349 FINISHED
Object Guan
Guan are a West African ethnolinguistic group primarily found in Ghana and neighboring countries, known for their diverse languages and long-established presence in the region.
 E1551230 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: Guan | Statement: [Guan peoples, ethnolinguisticGroup, Guan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Guan
Context triple: [Guan peoples, ethnolinguisticGroup, Guan]
  • A. Guan
    Guan is a common Chinese surname with historical roots and multiple romanized variants, including Kwan.
  • B. Ganlu
    Ganlu was a historical Chinese era name used during the Cao Wei state of the Three Kingdoms period.
  • C. Gao
    Gao is a Chinese surname historically associated with the Jewish community of Kaifeng, one of the oldest Jewish diasporas in China.
  • D. Gao
    Gao is a historic city in eastern Mali that served as a major trading center and former capital of the Songhai Empire along the Niger River.
  • E. Gao
    Gao is an Oceanic language of the Southeast Solomonic group spoken in the Solomon Islands.
  • 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: Guan
Triple: [Guan peoples, ethnolinguisticGroup, Guan]
Generated description
Guan are a West African ethnolinguistic group primarily found in Ghana and neighboring countries, known for their diverse languages and long-established presence in the region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Guan
Target entity description: Guan are a West African ethnolinguistic group primarily found in Ghana and neighboring countries, known for their diverse languages and long-established presence in the region.
  • A. Guan
    Guan is a common Chinese surname with historical roots and multiple romanized variants, including Kwan.
  • B. Ganlu
    Ganlu was a historical Chinese era name used during the Cao Wei state of the Three Kingdoms period.
  • C. Gao
    Gao is a Chinese surname historically associated with the Jewish community of Kaifeng, one of the oldest Jewish diasporas in China.
  • D. Gao
    Gao is a historic city in eastern Mali that served as a major trading center and former capital of the Songhai Empire along the Niger River.
  • E. Gao
    Gao is an Oceanic language of the Southeast Solomonic group spoken in the Solomon Islands.
  • 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_69e2454fc984819088213b58ee87a002 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f17910deb48190b38174e16868f3dd completed April 29, 2026, 3:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b7ee1fa788190b7589af0c049f6e5 completed May 18, 2026, 9:04 p.m.
NEDg Description generation batch_6a0b834f488c8190bee40bd1caea0e40 completed May 18, 2026, 9:23 p.m.
NED2 Entity disambiguation (via description) batch_6a0b8717b65c819089d29c1802d1ed55 completed May 18, 2026, 9:39 p.m.
Created at: April 17, 2026, 3:19 p.m.