Triple

T9937328
Position Surface form Disambiguated ID Type / Status
Subject In the Land of Blood and Honey E193989 entity
Predicate mainCharacter P1183 FINISHED
Object Ajla
Ajla is the Bosnian Muslim woman who serves as the central protagonist in Angelina Jolie’s war drama film "In the Land of Blood and Honey."
 E830888 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: Ajla | Statement: [In the Land of Blood and Honey, mainCharacter, Ajla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ajla
Context triple: [In the Land of Blood and Honey, mainCharacter, Ajla]
  • A. Dijlah
    Dijlah is the Arabic name for the Tigris River, one of the major rivers of Western Asia flowing through Turkey, Syria, and Iraq.
  • B. Awjila
    Awjila is an endangered Eastern Berber language once spoken in the oasis town of Awjila in northeastern Libya.
  • C. Suleja
    Suleja is a town in Niger State, Nigeria, located near the capital Abuja and known as a key gateway between the capital region and the country’s northwestern areas.
  • D. Munirka
    Munirka is a densely populated residential and commercial neighborhood in South Delhi, known for its urban village character, proximity to major institutions, and extensive rental housing.
  • E. Jajrud
    Jajrud is a river in northern Iran that flows through the Alborz Mountains toward the Tehran region.
  • 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: Ajla
Triple: [In the Land of Blood and Honey, mainCharacter, Ajla]
Generated description
Ajla is the Bosnian Muslim woman who serves as the central protagonist in Angelina Jolie’s war drama film "In the Land of Blood and Honey."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ajla
Target entity description: Ajla is the Bosnian Muslim woman who serves as the central protagonist in Angelina Jolie’s war drama film "In the Land of Blood and Honey."
  • A. Dijlah
    Dijlah is the Arabic name for the Tigris River, one of the major rivers of Western Asia flowing through Turkey, Syria, and Iraq.
  • B. Awjila
    Awjila is an endangered Eastern Berber language once spoken in the oasis town of Awjila in northeastern Libya.
  • C. Suleja
    Suleja is a town in Niger State, Nigeria, located near the capital Abuja and known as a key gateway between the capital region and the country’s northwestern areas.
  • D. Munirka
    Munirka is a densely populated residential and commercial neighborhood in South Delhi, known for its urban village character, proximity to major institutions, and extensive rental housing.
  • E. Jajrud
    Jajrud is a river in northern Iran that flows through the Alborz Mountains toward the Tehran region.
  • 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_69ca82e409348190a393777356b80a2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb5e4e19881909879b394090d6629 completed April 2, 2026, 12:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69d228f259b081909ce8a90ec1adad0d completed April 5, 2026, 9:18 a.m.
NEDg Description generation batch_69d22a78819481908ccff34730464f19 completed April 5, 2026, 9:25 a.m.
NED2 Entity disambiguation (via description) batch_69d22b0fea588190a4928c361c2367ca completed April 5, 2026, 9:27 a.m.
Created at: March 30, 2026, 8:44 p.m.