Triple

T8532597
Position Surface form Disambiguated ID Type / Status
Subject Guangzhou Metro Line 7 E201990 entity
Predicate hasStation P35 FINISHED
Object Shawan
Shawan is a metro station on Guangzhou's Line 7 serving the Shawan area in Guangzhou, China.
 E740230 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: Shawan | Statement: [Guangzhou Metro Line 7, hasStation, Shawan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shawan
Context triple: [Guangzhou Metro Line 7, hasStation, Shawan]
  • A. Shobab
    Shobab is a lesser-known son of King David of Israel and Bathsheba, mentioned briefly in the Hebrew Bible.
  • B. Shawar
    Shawar was a 12th-century vizier of the Fatimid Caliphate in Egypt, known for his turbulent rule and role in the conflicts that devastated Fustat.
  • C. Shuaib
    Shuaib is a prophet in Islamic tradition, often identified with the biblical Jethro and known for preaching justice and honesty to the people of Midian.
  • D. Bawshar
    Bawshar is a district in Muscat, Oman, known as a major urban area that includes important landmarks, commercial centers, and residential neighborhoods.
  • E. Khalil
    Khalil is a music producer best known for his work on the project "The King & I."
  • 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: Shawan
Triple: [Guangzhou Metro Line 7, hasStation, Shawan]
Generated description
Shawan is a metro station on Guangzhou's Line 7 serving the Shawan area in Guangzhou, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shawan
Target entity description: Shawan is a metro station on Guangzhou's Line 7 serving the Shawan area in Guangzhou, China.
  • A. Shobab
    Shobab is a lesser-known son of King David of Israel and Bathsheba, mentioned briefly in the Hebrew Bible.
  • B. Shawar
    Shawar was a 12th-century vizier of the Fatimid Caliphate in Egypt, known for his turbulent rule and role in the conflicts that devastated Fustat.
  • C. Shuaib
    Shuaib is a prophet in Islamic tradition, often identified with the biblical Jethro and known for preaching justice and honesty to the people of Midian.
  • D. Bawshar
    Bawshar is a district in Muscat, Oman, known as a major urban area that includes important landmarks, commercial centers, and residential neighborhoods.
  • E. Khalil
    Khalil is a music producer best known for his work on the project "The King & I."
  • 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_69ca832355b08190b8b6a4ab4a4a3554 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe678fe448190a50c6b0d149b081f completed March 31, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d70f81881908ac784608ad7a2aa completed April 2, 2026, 1:21 p.m.
NEDg Description generation batch_69ce6e69213c8190add7eb9cc74b1a33 completed April 2, 2026, 1:26 p.m.
NED2 Entity disambiguation (via description) batch_69ce6f28ae6481909a8a13613f3eb5e0 completed April 2, 2026, 1:29 p.m.
Created at: March 30, 2026, 6:17 p.m.