Triple

T9925875
Position Surface form Disambiguated ID Type / Status
Subject Ministry of Intelligence of Iran E187919 entity
Predicate replaces P101 FINISHED
Object SAVAMA E499632 NE FINISHED

How this triple was built (2 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: [Ministry of Intelligence of Iran, replaces, SAVAMA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SAVAMA
Context triple: [Ministry of Intelligence of Iran, replaces, SAVAMA]
  • A. SAVAMA chosen
    SAVAMA was the post-revolution Iranian intelligence and security organization that succeeded the Shah’s notorious secret police, SAVAK.
  • B. SAV
    SAV is the National Rail station code for Stratford-upon-Avon railway station in Warwickshire, England.
  • C. SAVC
    SAVC is the ICAO airport code for General Enrique Mosconi International Airport in Comodoro Rivadavia, Argentina.
  • D. 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.
  • E. SAVP
    SAVP is a profile or configuration associated with the Real-time Transport Protocol (RTP), typically used to define specific parameters or behaviors for secure or specialized media streaming sessions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82b22a688190b52c75bd48429c10 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb599e32c8190ac676fa89c131bb6 completed April 2, 2026, 12:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20e143660819097a9fa96365bc25a completed April 5, 2026, 7:24 a.m.
Created at: March 30, 2026, 8:43 p.m.