Triple

T31346997

Position	Surface form	Disambiguated ID	Type / Status
Subject	Judge Harry Pregerson Interchange	`E799472`	entity
Predicate	officialNameHonors	`P116229`	FINISHED
Object	Judge Harry Pregerson Judge Harry Pregerson was a long-serving and notably liberal judge on the U.S. Court of Appeals for the Ninth Circuit, recognized for his strong emphasis on fairness and compassion in the law.	`E1958428`	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: Judge Harry Pregerson | Statement: [Judge Harry Pregerson Interchange, officialNameHonors, Judge Harry Pregerson]

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: Judge Harry Pregerson
Triple: [Judge Harry Pregerson Interchange, officialNameHonors, Judge Harry Pregerson]

Generated description

Judge Harry Pregerson was a long-serving and notably liberal judge on the U.S. Court of Appeals for the Ninth Circuit, recognized for his strong emphasis on fairness and compassion in the law.

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

Target predicate: officialNameHonors
Context triple: [Judge Harry Pregerson Interchange, officialNameHonors, Judge Harry Pregerson]

A. nameHonors
Indicates that a name is given to honor, commemorate, or pay tribute to a particular entity.
B. namedInHonorBy chosen
Indicates that one entity has been used as the namesake or dedicatee by another entity, signifying that the latter is named in honor of the former.
C. alsoHonoredAs
Indicates that an entity is additionally recognized or celebrated under another title, role, or form of honor beyond its primary designation.
D. officialNameGivenBy
Indicates that an official or formal name has been assigned to an entity by a specific authority or source.
E. officialName
Indicates the formally recognized name assigned to an entity by an authoritative body or source.
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_69f224e51614819083141459a080e97c`	completed	April 29, 2026, 3:33 p.m.
NER	Named-entity recognition	`batch_69fec25f0fc48190b87ab1f9cd1eb0de`	completed	May 9, 2026, 5:13 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a2a721ad288819086c24cf4cb790dab`	completed	June 11, 2026, 8:30 a.m.
NEDg	Description generation	`batch_6a2a72e428ac8190a375710906f08dfb`	completed	June 11, 2026, 8:33 a.m.
NED2	Entity disambiguation (via description)	`batch_6a2a93b1ab148190897e05b560a79885`	completed	June 11, 2026, 10:53 a.m.
PD	Predicate disambiguation	`batch_69fec079a770819098df7cc3049df954`	completed	May 9, 2026, 5:04 a.m.

Created at: April 29, 2026, 9:17 p.m.