Triple

T13917410
Position Surface form Disambiguated ID Type / Status
Subject Otrar E334657 entity
Predicate alsoKnownAs P39 FINISHED
Object Farab
Farab is the historical name of Otrar, an important medieval Central Asian city that was a key Silk Road trading and cultural center.
 E1070302 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: Farab | Statement: [Otrar, alsoKnownAs, Farab]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Farab
Context triple: [Otrar, alsoKnownAs, Farab]
  • A. Fazza
    Fazza is the popular pen name of Sheikh Hamdan bin Mohammed Al Maktoum, the Crown Prince of Dubai and a well-known Emirati poet and public figure.
  • B. Farhual
    Farhual is a regional dialect of the Hakha Chin language spoken by Chin communities in parts of Myanmar and neighboring areas.
  • C. Farap
    Farap is a town in eastern Turkmenistan that serves as an important border crossing and transport hub between Turkmenistan and Uzbekistan.
  • D. Fayiz
    Fayiz is a masculine given name of Arabic origin, commonly used as a variant transliteration of the name Fayez.
  • E. Faiha
    Faiha is a residential district in Kuwait City known for its planned layout, community facilities, and central location within the capital.
  • 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: Farab
Triple: [Otrar, alsoKnownAs, Farab]
Generated description
Farab is the historical name of Otrar, an important medieval Central Asian city that was a key Silk Road trading and cultural center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Farab
Target entity description: Farab is the historical name of Otrar, an important medieval Central Asian city that was a key Silk Road trading and cultural center.
  • A. Fazza
    Fazza is the popular pen name of Sheikh Hamdan bin Mohammed Al Maktoum, the Crown Prince of Dubai and a well-known Emirati poet and public figure.
  • B. Farhual
    Farhual is a regional dialect of the Hakha Chin language spoken by Chin communities in parts of Myanmar and neighboring areas.
  • C. Farap
    Farap is a town in eastern Turkmenistan that serves as an important border crossing and transport hub between Turkmenistan and Uzbekistan.
  • D. Fayiz
    Fayiz is a masculine given name of Arabic origin, commonly used as a variant transliteration of the name Fayez.
  • E. Faiha
    Faiha is a residential district in Kuwait City known for its planned layout, community facilities, and central location within the capital.
  • 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_69d81c5f739081908bc05b2461f54828 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de272753e48190bc609482635280ff completed April 14, 2026, 11:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce7a1c388190a57dfdbbb732bbcb completed May 3, 2026, 10:38 p.m.
NEDg Description generation batch_69f9fd56da288190b2bd33bc496c3fb9 completed May 5, 2026, 2:23 p.m.
NED2 Entity disambiguation (via description) batch_69fb039fdb1c8190ad5286d1cfe80a29 completed May 6, 2026, 9:02 a.m.
Created at: April 9, 2026, 10:16 p.m.