Triple

T11698308
Position Surface form Disambiguated ID Type / Status
Subject CB2 receptor E278052 entity
Predicate hasOrthologIn P51609 FINISHED
Object rat Cnr2
Rat Cnr2 is the rat gene encoding the cannabinoid receptor type 2 (CB2), a G protein–coupled receptor involved in modulating immune and inflammatory responses.
 E939679 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: rat Cnr2 | Statement: [CB2 receptor, hasOrthologIn, rat Cnr2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: rat Cnr2
Context triple: [CB2 receptor, hasOrthologIn, rat Cnr2]
  • A. C2r
    C2r is the standard magnetic polarity chron code assigned to the Gauss–Matuyama geomagnetic reversal interval in the geomagnetic polarity timescale.
  • B. CNR
    CNR is an acronym commonly used for the College of Natural Resources, an academic unit focused on environmental science, resource management, and related fields.
  • C. CNR
    CNR is the stock ticker symbol for Canadian National Railway, a major North American freight railway company.
  • D. R2N
    R2N is the symbol used to designate the R2 Nord commuter rail line in the Barcelona suburban railway network.
  • E. RANC
    RANC is the Royal Australian Navy’s principal officer training institution, responsible for educating and preparing naval officers for service.
  • 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: rat Cnr2
Triple: [CB2 receptor, hasOrthologIn, rat Cnr2]
Generated description
Rat Cnr2 is the rat gene encoding the cannabinoid receptor type 2 (CB2), a G protein–coupled receptor involved in modulating immune and inflammatory responses.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: rat Cnr2
Target entity description: Rat Cnr2 is the rat gene encoding the cannabinoid receptor type 2 (CB2), a G protein–coupled receptor involved in modulating immune and inflammatory responses.
  • A. C2r
    C2r is the standard magnetic polarity chron code assigned to the Gauss–Matuyama geomagnetic reversal interval in the geomagnetic polarity timescale.
  • B. CNR
    CNR is an acronym commonly used for the College of Natural Resources, an academic unit focused on environmental science, resource management, and related fields.
  • C. CNR
    CNR is the stock ticker symbol for Canadian National Railway, a major North American freight railway company.
  • D. R2N
    R2N is the symbol used to designate the R2 Nord commuter rail line in the Barcelona suburban railway network.
  • E. RANC
    RANC is the Royal Australian Navy’s principal officer training institution, responsible for educating and preparing naval officers for service.
  • 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_69d6aafe02d881909900d54ad7d4af84 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a47df68c81908a91919a69b4880d completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef147e2e10819085eaed83fd955b6b completed April 27, 2026, 7:47 a.m.
NEDg Description generation batch_69ef3553a1748190b554463bcea8bd1d completed April 27, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69ef51fe3824819099f440426d3e6888 completed April 27, 2026, 12:09 p.m.
Created at: April 8, 2026, 9:40 p.m.