Triple

T34491875

Position	Surface form	Disambiguated ID	Type / Status
Subject	Larkin Company	`E885488`	entity
Predicate	hadWarehouseComplex	`P3676`	FINISHED
Object	Larkin Terminal Warehouse Larkin Terminal Warehouse was a large industrial storage and distribution facility associated with the historic Larkin Company complex in Buffalo, New York.	`E2099303`	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: Larkin Terminal Warehouse | Statement: [Larkin Company, hadWarehouseComplex, Larkin Terminal Warehouse]

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: Larkin Terminal Warehouse
Triple: [Larkin Company, hadWarehouseComplex, Larkin Terminal Warehouse]

Generated description

Larkin Terminal Warehouse was a large industrial storage and distribution facility associated with the historic Larkin Company complex in Buffalo, New York.

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

Target predicate: hadWarehouseComplex
Context triple: [Larkin Company, hadWarehouseComplex, Larkin Terminal Warehouse]

A. warehouseType
Indicates the specific category or classification of a warehouse based on its function, storage characteristics, or operational role.
B. warehouseUse
Indicates that an entity is used or designated for warehouse-related functions such as storage, handling, or distribution of goods.
C. storageFacility chosen
Indicates a relationship where one entity serves as a place or facility used to store another entity or its items.
D. hadWorkhouse
Indicates that an entity possessed, operated, or was associated with a workhouse.
E. hadCustom
Indicates that an entity previously possessed or was associated with a customized or user-defined version of something.
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_69f349cafcec8190997b45b3fdc16c27`	completed	April 30, 2026, 12:23 p.m.
NER	Named-entity recognition	`batch_69f71fb1ab3881908e2f7c0e6f23db49`	completed	May 3, 2026, 10:13 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a37214195288190aeb1dd22cf41cb72`	completed	June 20, 2026, 11:24 p.m.
NEDg	Description generation	`batch_6a372200430c8190a70e010e1c3cad77`	completed	June 20, 2026, 11:28 p.m.
NED2	Entity disambiguation (via description)	`batch_6a37230e5a448190a0915ebeada6edd2`	completed	June 20, 2026, 11:32 p.m.
PD	Predicate disambiguation	`batch_69f71cc6397881909aaad37a9daa8a7e`	completed	May 3, 2026, 10 a.m.

Created at: May 1, 2026, 2:01 a.m.