Triple

T38502970

Position	Surface form	Disambiguated ID	Type / Status
Subject	Brian Lackey	`E919889`	entity
Predicate	sharesChildhoodTeamWith	`P202901`	FINISHED
Object	Neil McCormick Neil McCormick is a character best known as one of the two boys whose intertwined childhood experiences and later lives are explored in the film and novel "Mysterious Skin."	`E2105715`	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: Neil McCormick | Statement: [Brian Lackey, sharesChildhoodTeamWith, Neil McCormick]

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: Neil McCormick
Triple: [Brian Lackey, sharesChildhoodTeamWith, Neil McCormick]

Generated description

Neil McCormick is a character best known as one of the two boys whose intertwined childhood experiences and later lives are explored in the film and novel "Mysterious Skin."

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

Target predicate: sharesChildhoodTeamWith
Context triple: [Brian Lackey, sharesChildhoodTeamWith, Neil McCormick]

A. sharesChildrenWith
Indicates that two entities are co-parents, having one or more children in common.
B. associatedWithParentTeam
Indicates that an entity is linked or connected to a higher-level or parent team in an organizational or hierarchical structure.
C. playedForJuniorTeam
Indicates that an individual was a member of and played for a specific junior-level sports team.
D. hasYouthTeam
Indicates that an entity has an associated youth team that serves as its junior or developmental squad.
E. parentLeagueTeam
Indicates that a team competes within, or is organizationally part of, a specific parent league.
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_69f76e9ddd4481908f8c04439d848f9d`	completed	May 3, 2026, 3:49 p.m.
NER	Named-entity recognition	`batch_6a00ccadb6908190ab810a7c05315fa8`	completed	May 10, 2026, 6:21 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a41e0222e5c81909ec8e912dee4cf0b`	completed	June 29, 2026, 3:01 a.m.
NEDg	Description generation	`batch_6a41e11942e0819097a50a0d265f5b2f`	completed	June 29, 2026, 3:06 a.m.
NED2	Entity disambiguation (via description)	`batch_6a41e1819f888190be682921759b1ffe`	completed	June 29, 2026, 3:07 a.m.
PD	Predicate disambiguation	`batch_6a00cc0f86b88190a0d2c43618558f86`	completed	May 10, 2026, 6:18 p.m.
PDg	Predicate description generation	`batch_6a00ccabfe8c8190be7c2bafe2323c2b`	completed	May 10, 2026, 6:21 p.m.

Created at: May 3, 2026, 4:31 p.m.