Triple

T27834365

Position	Surface form	Disambiguated ID	Type / Status
Subject	Whip Whitaker	`E703185`	entity
Predicate	becomesEmotionallyInvolvedWith	`P23414`	FINISHED
Object	Nicole Nicole is a troubled young woman struggling with drug addiction who forms a complex emotional relationship with airline pilot Whip Whitaker in the film "Flight."	`E1793188`	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: Nicole | Statement: [Whip Whitaker, becomesEmotionallyInvolvedWith, Nicole]

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: Nicole
Triple: [Whip Whitaker, becomesEmotionallyInvolvedWith, Nicole]

Generated description

Nicole is a troubled young woman struggling with drug addiction who forms a complex emotional relationship with airline pilot Whip Whitaker in the film "Flight."

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

Target predicate: becomesEmotionallyInvolvedWith
Context triple: [Whip Whitaker, becomesEmotionallyInvolvedWith, Nicole]

A. emotionallyAttachedTo chosen
Indicates that one entity has a strong emotional bond, affection, or dependence directed toward another entity.
B. emotionalFocusOf
Indicates that one entity is the primary target or center of another entity’s emotions or emotional attention.
C. closelyInvolvedWith
Indicates a relationship in which one entity is deeply and actively engaged with another’s activities, decisions, or affairs.
D. emotionalDynamic
Indicates how emotions, moods, or affective states change, interact, or influence each other between entities over time.
E. inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
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_69ef840b94b08190950a4f77296938b2`	completed	April 27, 2026, 3:43 p.m.
NER	Named-entity recognition	`batch_69f6389eedac81908f57d172088d394d`	completed	May 2, 2026, 5:47 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a13034767888190a7317b8baf7895b5`	completed	May 24, 2026, 1:55 p.m.
NEDg	Description generation	`batch_6a1303e852488190ad34cae264ed7752`	completed	May 24, 2026, 1:58 p.m.
NED2	Entity disambiguation (via description)	`batch_6a130498a5748190bf5560d2cc95f478`	completed	May 24, 2026, 2 p.m.
PD	Predicate disambiguation	`batch_69f6318ae6f08190b3f85f9201046a15`	completed	May 2, 2026, 5:16 p.m.

Created at: April 27, 2026, 5:58 p.m.