Triple

T33407377

Position	Surface form	Disambiguated ID	Type / Status
Subject	Richard Speck	`E855472`	entity
Predicate	survivingWitness	`P177617`	FINISHED
Object	Corazon Amurao Corazon Amurao is a Filipina nurse who survived and later testified against American mass murderer Richard Speck after his 1966 killing spree in Chicago.	`E2048793`	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: Corazon Amurao | Statement: [Richard Speck, survivingWitness, Corazon Amurao]

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: Corazon Amurao
Triple: [Richard Speck, survivingWitness, Corazon Amurao]

Generated description

Corazon Amurao is a Filipina nurse who survived and later testified against American mass murderer Richard Speck after his 1966 killing spree in Chicago.

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

Target predicate: survivingWitness
Context triple: [Richard Speck, survivingWitness, Corazon Amurao]

A. witnesses
Indicates that one entity observes an event, action, or situation involving another entity, typically as a bystander or observer.
B. isSurvivorOf
Indicates that one entity has lived through, endured, or remained alive after a particular event, condition, or harmful circumstance involving another entity.
C. survivesWith
Indicates that one entity continues to live, endure, or remain viable in the presence, context, or company of another entity.
D. savedByTestimonyOf
Indicates that an entity is rescued, delivered, or brought to salvation as a result of another entity’s testimony or witness.
E. onlyWitnessOf
Indicates that one entity is the sole witness to an event, action, or situation involving another entity, with no other witnesses present.
F. None of above. chosen

Provenance (7 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_69f3496f04a08190804e56ac5098b8e4`	completed	April 30, 2026, 12:22 p.m.
NER	Named-entity recognition	`batch_69f7009d39508190af7301f824615e88`	completed	May 3, 2026, 8 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a3576fabb6881908f22d1fab8ed7e13`	completed	June 19, 2026, 5:06 p.m.
NEDg	Description generation	`batch_6a35776bbb3c8190bda2a14ef5abdaf8`	completed	June 19, 2026, 5:07 p.m.
NED2	Entity disambiguation (via description)	`batch_6a3577e82568819091390ca6df3cf66e`	completed	June 19, 2026, 5:10 p.m.
PD	Predicate disambiguation	`batch_69f6fc5740fc81909774a4f65201a3ff`	completed	May 3, 2026, 7:42 a.m.
PDg	Predicate description generation	`batch_69f6ffb7554881908993d6d2ffbcf8f5`	completed	May 3, 2026, 7:56 a.m.

Created at: May 1, 2026, 1:36 a.m.