Triple

T5168572
Position Surface form Disambiguated ID Type / Status
Subject SAVAK E116617 entity
Predicate replacedBy P101 FINISHED
Object SAVAMA
SAVAMA was the post-revolution Iranian intelligence and security organization that succeeded the Shah’s notorious secret police, SAVAK.
 E499632 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: SAVAMA | Statement: [SAVAK, replacedBy, SAVAMA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SAVAMA
Context triple: [SAVAK, replacedBy, SAVAMA]
  • A. SAV
    SAV is the National Rail station code for Stratford-upon-Avon railway station in Warwickshire, England.
  • B. sva
    sva is the ISO 639-3 code for the Svan language, a Kartvelian language spoken by the Svan people in the Svaneti region of northwestern Georgia.
  • C. SAU
    SAU is an international university established by the South Asian Association for Regional Cooperation (SAARC) in New Delhi, India, focusing on postgraduate and doctoral education and research for students from South Asian countries.
  • D. SAU
    SAU is the three-letter ISO 3166-1 alpha-3 country code assigned to Saudi Arabia.
  • E. SAVAK
    SAVAK was the notorious secret police and intelligence organization of Iran under Shah Mohammad Reza Pahlavi, known for its widespread surveillance, repression, and human rights abuses.
  • 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: SAVAMA
Triple: [SAVAK, replacedBy, SAVAMA]
Generated description
SAVAMA was the post-revolution Iranian intelligence and security organization that succeeded the Shah’s notorious secret police, SAVAK.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SAVAMA
Target entity description: SAVAMA was the post-revolution Iranian intelligence and security organization that succeeded the Shah’s notorious secret police, SAVAK.
  • A. SAV
    SAV is the National Rail station code for Stratford-upon-Avon railway station in Warwickshire, England.
  • B. sva
    sva is the ISO 639-3 code for the Svan language, a Kartvelian language spoken by the Svan people in the Svaneti region of northwestern Georgia.
  • C. SAU
    SAU is an international university established by the South Asian Association for Regional Cooperation (SAARC) in New Delhi, India, focusing on postgraduate and doctoral education and research for students from South Asian countries.
  • D. SAU
    SAU is the three-letter ISO 3166-1 alpha-3 country code assigned to Saudi Arabia.
  • E. SAVAK
    SAVAK was the notorious secret police and intelligence organization of Iran under Shah Mohammad Reza Pahlavi, known for its widespread surveillance, repression, and human rights abuses.
  • 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_69bd445ff97c81909a2615cc56235470 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd794dd9988190922e138f2a9a3c62 completed March 20, 2026, 4:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed93f33ac8190b2f60a8e95685bc8 completed March 21, 2026, 5:45 p.m.
NEDg Description generation batch_69beda0419108190862d028a14227e8a completed March 21, 2026, 5:48 p.m.
NED2 Entity disambiguation (via description) batch_69bedaa232ac81908c5ee2d4ba8cbcd7 completed March 21, 2026, 5:51 p.m.
Created at: March 20, 2026, 1:45 p.m.