Triple

T2919113
Position Surface form Disambiguated ID Type / Status
Subject Zaydi Shia E78675 entity
Predicate hasSubSchool P14190 FINISHED
Object Tabiriyya
Tabiriyya is a sub-school within the Zaydi branch of Shia Islam, representing a distinct theological and legal tradition in that sect.
 E310262 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: Tabiriyya | Statement: [Zaydi Shia, hasSubSchool, Tabiriyya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tabiriyya
Context triple: [Zaydi Shia, hasSubSchool, Tabiriyya]
  • A. El Tebbin
    El Tebbin is an industrial district in southern Cairo, Egypt, known for its steel and heavy manufacturing facilities.
  • B. Taltal
    Taltal is a coastal city in northern Chile known for its historic mining activity and proximity to the Atacama Desert.
  • C. Rissala
    Rissala is a locality in Finland known primarily for hosting a major Finnish Air Force base associated with the Karelian Air Command.
  • D. Murzuq
    Murzuq is an oasis town in southwestern Libya that historically served as an important Saharan trade and caravan center in the Fezzan region.
  • E. Shuafat
    Shuafat is a Palestinian neighborhood and refugee camp in East Jerusalem known for its dense population, complex political status, and challenging living conditions.
  • 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: Tabiriyya
Triple: [Zaydi Shia, hasSubSchool, Tabiriyya]
Generated description
Tabiriyya is a sub-school within the Zaydi branch of Shia Islam, representing a distinct theological and legal tradition in that sect.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tabiriyya
Target entity description: Tabiriyya is a sub-school within the Zaydi branch of Shia Islam, representing a distinct theological and legal tradition in that sect.
  • A. El Tebbin
    El Tebbin is an industrial district in southern Cairo, Egypt, known for its steel and heavy manufacturing facilities.
  • B. Taltal
    Taltal is a coastal city in northern Chile known for its historic mining activity and proximity to the Atacama Desert.
  • C. Rissala
    Rissala is a locality in Finland known primarily for hosting a major Finnish Air Force base associated with the Karelian Air Command.
  • D. Murzuq
    Murzuq is an oasis town in southwestern Libya that historically served as an important Saharan trade and caravan center in the Fezzan region.
  • E. Shuafat
    Shuafat is a Palestinian neighborhood and refugee camp in East Jerusalem known for its dense population, complex political status, and challenging living conditions.
  • 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_69ad8b0c2ad081909ff87050ae542bb9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad96a53f8c8190b188d549f1161e84 completed March 8, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0562fc5f081909c9130f71f379a24 completed March 10, 2026, 5:34 p.m.
NEDg Description generation batch_69b06117ba088190886fa464f54525cd completed March 10, 2026, 6:21 p.m.
NED2 Entity disambiguation (via description) batch_69b0628d5f608190b7a13ac2e8b8d721 completed March 10, 2026, 6:27 p.m.
Created at: March 8, 2026, 2:54 p.m.