Triple

T26493233

Position	Surface form	Disambiguated ID	Type / Status
Subject	CalSTRS Chief Investment Officer	`E669213`	entity
Predicate	employerAcronym	`P118183`	FINISHED
Object	CalSTRS CalSTRS is the California State Teachers’ Retirement System, one of the largest public pension funds in the United States, providing retirement benefits to California’s public school educators.	`E1728189`	NE FINISHED

How this triple was built (3 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: CalSTRS | Statement: [CalSTRS Chief Investment Officer, employerAcronym, CalSTRS]

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: CalSTRS
Triple: [CalSTRS Chief Investment Officer, employerAcronym, CalSTRS]

Generated description

CalSTRS is the California State Teachers’ Retirement System, one of the largest public pension funds in the United States, providing retirement benefits to California’s public school educators.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: employerAcronym
Context triple: [CalSTRS Chief Investment Officer, employerAcronym, CalSTRS]

A. organizationAcronym chosen
Indicates that an organization is known or referred to by a specific acronym.
B. employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
C. employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
D. employerService
Indicates that one entity provides employment-related services or functions to another entity, typically in the role of an employer.
E. originalCompanyAbbreviation
Indicates that an abbreviation represents the shortened or initial-based form of an original company’s full name.
F. None of above.

Provenance (6 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_69eeb319007081909642b414b114b35a`	completed	April 27, 2026, 12:51 a.m.
NER	Named-entity recognition	`batch_69f657f653448190a945b4751af8507d`	completed	May 2, 2026, 8 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a11bb2d478c819081a1e44a76c1ca2a`	completed	May 23, 2026, 2:35 p.m.
NEDg	Description generation	`batch_6a11be60f78c819093363b32bd4e3447`	completed	May 23, 2026, 2:49 p.m.
NED2	Entity disambiguation (via description)	`batch_6a11bf9449b08190bcaff036e81d9392`	completed	May 23, 2026, 2:54 p.m.
PD	Predicate disambiguation	`batch_69f6575ba12081909396036f78757a76`	completed	May 2, 2026, 7:58 p.m.

Created at: April 27, 2026, 1:06 a.m.