Triple

T28089150

Position	Surface form	Disambiguated ID	Type / Status
Subject	federal social security courts of Argentina	`E709906`	entity
Predicate	abbreviationOfPrimaryRespondent	`P76463`	FINISHED
Object	ANSES ANSES is Argentina’s National Social Security Administration, the federal agency responsible for managing pensions, family allowances, and other social security benefits.	`E1801323`	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: ANSES | Statement: [federal social security courts of Argentina, abbreviationOfPrimaryRespondent, ANSES]

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: ANSES
Triple: [federal social security courts of Argentina, abbreviationOfPrimaryRespondent, ANSES]

Generated description

ANSES is Argentina’s National Social Security Administration, the federal agency responsible for managing pensions, family allowances, and other social security benefits.

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

Target predicate: abbreviationOfPrimaryRespondent
Context triple: [federal social security courts of Argentina, abbreviationOfPrimaryRespondent, ANSES]

A. respondentAbbreviation chosen
Indicates that one entity is an abbreviated or shortened form of the name or designation of the respondent entity.
B. abbreviationOfPrimaryCustomer
Indicates that one entity is an abbreviation or shortened form of the name or identifier of the primary customer entity.
C. defendantAbbreviation
Indicates that one entity is an abbreviated or shortened form of the name or designation of a defendant in a legal context.
D. perpetratorAbbreviation
Indicates that one entity is an abbreviated or shortened form used to refer to the perpetrator of an action or offense.
E. abbreviationOfInvestigator
Indicates that one identifier or name is an abbreviated form of the full name of an investigator.
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_69ef9b7037f0819095bb90eaccbcaf32`	completed	April 27, 2026, 5:22 p.m.
NER	Named-entity recognition	`batch_69f64dbbaefc8190952b8320bf4397d8`	completed	May 2, 2026, 7:17 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a15c91cfdf88190883331d8a14e58cf`	completed	May 26, 2026, 4:23 p.m.
NEDg	Description generation	`batch_6a15c994a74c8190aa39a3a00d374f71`	completed	May 26, 2026, 4:25 p.m.
NED2	Entity disambiguation (via description)	`batch_6a15ca0b3b148190b6d294ff8904aaa5`	completed	May 26, 2026, 4:27 p.m.
PD	Predicate disambiguation	`batch_69f64cacd2c08190aed8a1761d0da679`	completed	May 2, 2026, 7:12 p.m.

Created at: April 27, 2026, 8:57 p.m.