Triple

T6107502
Position Surface form Disambiguated ID Type / Status
Subject PepsiCo E136151 entity
Predicate tickerSymbol P1447 FINISHED
Object PEP
PEP is the stock ticker symbol for PepsiCo, the multinational food, snack, and beverage corporation traded on the NASDAQ.
 E568789 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: PEP | Statement: [PepsiCo, tickerSymbol, PEP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PEP
Context triple: [PepsiCo, tickerSymbol, PEP]
  • A. PEPs
    PEPs are formal design documents that propose and describe new features, processes, or changes for the Python programming language and its community.
  • B. PEP 1
    PEP 1 is the foundational Python Enhancement Proposal that defines the purpose, structure, and workflow for all other PEPs in the Python community process.
  • C. PEP 0
    PEP 0 is the index document that lists and tracks the status of all Python Enhancement Proposals (PEPs) in the Python community.
  • D. Pep
    Pep is the widely used nickname of Josep "Pep" Guardiola, the renowned Spanish football manager and former player.
  • E. Pe
    Pe is a Hebrew consonant letter that represents a "p" or "f" sound and has both standard and final written forms.
  • 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: PEP
Triple: [PepsiCo, tickerSymbol, PEP]
Generated description
PEP is the stock ticker symbol for PepsiCo, the multinational food, snack, and beverage corporation traded on the NASDAQ.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PEP
Target entity description: PEP is the stock ticker symbol for PepsiCo, the multinational food, snack, and beverage corporation traded on the NASDAQ.
  • A. PEPs
    PEPs are formal design documents that propose and describe new features, processes, or changes for the Python programming language and its community.
  • B. PEP 1
    PEP 1 is the foundational Python Enhancement Proposal that defines the purpose, structure, and workflow for all other PEPs in the Python community process.
  • C. PEP 0
    PEP 0 is the index document that lists and tracks the status of all Python Enhancement Proposals (PEPs) in the Python community.
  • D. Pep
    Pep is the widely used nickname of Josep "Pep" Guardiola, the renowned Spanish football manager and former player.
  • E. Pe
    Pe is a Hebrew consonant letter that represents a "p" or "f" sound and has both standard and final written forms.
  • 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_69c0087dee9881909e3655be88208c01 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05b81fad081909b622cafc6d51249 completed March 22, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1255b27a88190b45b664a2ba41166 completed March 23, 2026, 11:34 a.m.
NEDg Description generation batch_69c125ede4f88190989a5a40accd2745 completed March 23, 2026, 11:37 a.m.
NED2 Entity disambiguation (via description) batch_69c1268ffc7481909a9bd2be039dbf45 completed March 23, 2026, 11:40 a.m.
Created at: March 22, 2026, 4:13 p.m.