Triple

T35563250

Position	Surface form	Disambiguated ID	Type / Status
Subject	The West Point Story	`E1027693`	entity
Predicate	castMember	`P1668`	FINISHED
Object	Phil Carey Phil Carey was an American actor best known for his rugged roles in Westerns and for his long-running portrayal of Asa Buchanan on the soap opera "One Life to Live."	`E2150205`	NE FINISHED

How this triple was built (2 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: Phil Carey | Statement: [The West Point Story, castMember, Phil Carey]

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: Phil Carey
Triple: [The West Point Story, castMember, Phil Carey]

Generated description

Phil Carey was an American actor best known for his rugged roles in Westerns and for his long-running portrayal of Asa Buchanan on the soap opera "One Life to Live."

Provenance (5 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_69f76e020fd8819081cb080e7e203083`	completed	May 3, 2026, 3:47 p.m.
NER	Named-entity recognition	`batch_69f7987b81a881908e2b0877be6f0449`	completed	May 3, 2026, 6:48 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a38683d20c0819090c219eebbb1bddc`	completed	June 21, 2026, 10:39 p.m.
NEDg	Description generation	`batch_6a386c1a57d08190a1dd59e8ea1181df`	completed	June 21, 2026, 10:56 p.m.
NED2	Entity disambiguation (via description)	`batch_6a386c714e348190887419b46c7850ed`	completed	June 21, 2026, 10:57 p.m.

Created at: May 3, 2026, 4:04 p.m.