Triple

T5890784
Position Surface form Disambiguated ID Type / Status
Subject Corpus Inscriptionum Latinarum E130981 entity
Predicate hasPart P35 FINISHED
Object CIL I
CIL I is the first volume of the Corpus Inscriptionum Latinarum, containing a foundational collection of early Latin inscriptions.
 E552343 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: CIL I | Statement: [Corpus Inscriptionum Latinarum, hasPart, CIL I]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CIL I
Context triple: [Corpus Inscriptionum Latinarum, hasPart, CIL I]
  • A. CIC
    CIC is the commonly used abbreviation for the Cement Industry Committee, an organization associated with the cement sector.
  • B. CIC
    CIC is the three-letter IATA airport code assigned to Chico Municipal Airport in Chico, California.
  • C. ILCS
    ILCS is the abbreviation for the Illinois Compiled Statutes, the codified collection of the general and permanent laws of the state of Illinois.
  • D. CIRO
    CIRO is Japan’s Cabinet Intelligence and Research Office, a central government agency responsible for gathering, analyzing, and coordinating national intelligence for the Prime Minister and cabinet.
  • E. CRIL (IC17)
    CRIL (IC17) is a major Lisbon ring road and motorway that helps divert traffic around the city and connect several key suburbs and highways.
  • 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: CIL I
Triple: [Corpus Inscriptionum Latinarum, hasPart, CIL I]
Generated description
CIL I is the first volume of the Corpus Inscriptionum Latinarum, containing a foundational collection of early Latin inscriptions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CIL I
Target entity description: CIL I is the first volume of the Corpus Inscriptionum Latinarum, containing a foundational collection of early Latin inscriptions.
  • A. CIC
    CIC is the three-letter IATA airport code assigned to Chico Municipal Airport in Chico, California.
  • B. CIC
    CIC is the commonly used abbreviation for the Cement Industry Committee, an organization associated with the cement sector.
  • C. ILCS
    ILCS is the abbreviation for the Illinois Compiled Statutes, the codified collection of the general and permanent laws of the state of Illinois.
  • D. CIRO
    CIRO is Japan’s Cabinet Intelligence and Research Office, a central government agency responsible for gathering, analyzing, and coordinating national intelligence for the Prime Minister and cabinet.
  • E. CRIL (IC17)
    CRIL (IC17) is a major Lisbon ring road and motorway that helps divert traffic around the city and connect several key suburbs and highways.
  • 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_69c00857439c819095950754176aa58a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c036b228508190b050acf51860a5c2 completed March 22, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b14c2ff081908243988d5815be6d completed March 23, 2026, 3:19 a.m.
NEDg Description generation batch_69c0b1fabe448190be7d93b1f8c17c2a completed March 23, 2026, 3:22 a.m.
NED2 Entity disambiguation (via description) batch_69c0b29d6048819086c4d4cd01c64a51 completed March 23, 2026, 3:25 a.m.
Created at: March 22, 2026, 3:58 p.m.