Triple

T21192378
Position Surface form Disambiguated ID Type / Status
Subject MMS E522242 entity
Predicate hasComponent P35 FINISHED
Object MMS Relay/Server NE NERFINISHED

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: MMS Relay/Server | Statement: [MMS, hasComponent, MMS Relay/Server]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MMS Relay/Server
Context triple: [MMS, hasComponent, MMS Relay/Server]
  • A. MMS
    MMS is the Massachusetts Medical Society, a professional association representing physicians and medical students in Massachusetts and the publisher of the New England Journal of Medicine.
  • B. MMS chosen
    MMS (Multimedia Messaging Service) is a mobile messaging standard that allows users to send multimedia content such as images, audio, and video between mobile devices.
  • C. MMSM
    MMSM is the ICAO airport code assigned to Felipe Ángeles International Airport, a major commercial airport serving the Mexico City metropolitan area.
  • D. MMQT
    MMQT is the ICAO airport code for Querétaro International Airport in Querétaro, Mexico.
  • E. M2M
    M2M is a Norwegian pop duo best known for their late-1990s and early-2000s teen pop hits like "Don't Say You Love Me."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51061388190aa03f19700d3ef04 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73338dbe881908360dedad65c964b completed April 21, 2026, 8:20 a.m.
Created at: April 16, 2026, 3:07 p.m.