Triple

T10632612
Position Surface form Disambiguated ID Type / Status
Subject South Waziristan Agency E250494 entity
Predicate capital P234 FINISHED
Object Wana
Wana is a town in Pakistan’s Khyber Pakhtunkhwa province that serves as a key administrative and commercial center in the South Waziristan region.
 E876356 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: Wana | Statement: [South Waziristan Agency, capital, Wana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wana
Context triple: [South Waziristan Agency, capital, Wana]
  • A. Wau
    Wau is a town in Papua New Guinea historically notable as the site of a significant World War II battle between Allied and Japanese forces.
  • B. Waiyana
    Waiyana is an alternative name for the Wayana language, an indigenous Cariban language spoken by the Wayana people in parts of Brazil, Suriname, and French Guiana.
  • C. Suawa
    Suawa is an Austronesian language spoken by the Suwawa people of North Sulawesi, Indonesia.
  • D. Bawi
    Bawi was a Sasanian Persian military commander known for leading forces against the Byzantine Empire during the Iberian War in the 6th century.
  • E. Wajana
    Wajana is an alternative name for the Wayana language, an indigenous Cariban language spoken by the Wayana people in parts of Suriname, French Guiana, and Brazil.
  • 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: Wana
Triple: [South Waziristan Agency, capital, Wana]
Generated description
Wana is a town in Pakistan’s Khyber Pakhtunkhwa province that serves as a key administrative and commercial center in the South Waziristan region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wana
Target entity description: Wana is a town in Pakistan’s Khyber Pakhtunkhwa province that serves as a key administrative and commercial center in the South Waziristan region.
  • A. Wau
    Wau is a town in Papua New Guinea historically notable as the site of a significant World War II battle between Allied and Japanese forces.
  • B. Waiyana
    Waiyana is an alternative name for the Wayana language, an indigenous Cariban language spoken by the Wayana people in parts of Brazil, Suriname, and French Guiana.
  • C. Suawa
    Suawa is an Austronesian language spoken by the Suwawa people of North Sulawesi, Indonesia.
  • D. Bawi
    Bawi was a Sasanian Persian military commander known for leading forces against the Byzantine Empire during the Iberian War in the 6th century.
  • E. Wajana
    Wajana is an alternative name for the Wayana language, an indigenous Cariban language spoken by the Wayana people in parts of Suriname, French Guiana, and Brazil.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6df95f5e88190b34ce3ec972759ef completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96bbd64d8819089d55af875d39e45 completed April 10, 2026, 9:29 p.m.
NEDg Description generation batch_69d9701de92881908c0b8f05eae97e35 completed April 10, 2026, 9:48 p.m.
NED2 Entity disambiguation (via description) batch_69d970f3f78081909bcb2dae6dae06d5 completed April 10, 2026, 9:51 p.m.
Created at: April 8, 2026, 9:02 p.m.