Triple

T24115053

Position	Surface form	Disambiguated ID	Type / Status
Subject	Addington County	`E597485`	entity
Predicate	containsHistoricTownship	`P92098`	FINISHED
Object	Camden Township Camden Township is a historic rural municipality that once formed part of Addington County in eastern Ontario, Canada.	`E1616525`	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: Camden Township | Statement: [Addington County, containsHistoricTownship, Camden Township]

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: Camden Township
Triple: [Addington County, containsHistoricTownship, Camden Township]

Generated description

Camden Township is a historic rural municipality that once formed part of Addington County in eastern Ontario, Canada.

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

Target predicate: containsHistoricTownship
Context triple: [Addington County, containsHistoricTownship, Camden Township]

A. historicalTownshipOf chosen
Indicates that one entity was formerly a township encompassing or governing the other entity during a past historical period.
B. containsHistoricTown
Indicates that one entity geographically includes or encompasses a town that has recognized historical significance.
C. hasHistoricCountyTownRelation
Indicates a relationship where a town serves or has served as the historic county town (traditional administrative center) of a given county.
D. hasMarketTownHistory
Indicates that an entity has a historical association with functioning as a market town or possessing recognized market-town status in the past.
E. hasHistoricHamlets
Indicates that an entity possesses or is associated with one or more historically recognized hamlets.
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_69e288c74200819098ab875b592cb39f`	completed	April 17, 2026, 7:23 p.m.
NER	Named-entity recognition	`batch_69f1de1daf0481908767902bdf4e3682`	completed	April 29, 2026, 10:31 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a0f968c2bb48190a208248973e659ca`	completed	May 21, 2026, 11:34 p.m.
NEDg	Description generation	`batch_6a0f97690ba881908497a2b913a1703f`	completed	May 21, 2026, 11:38 p.m.
NED2	Entity disambiguation (via description)	`batch_6a0f9833113c81909228b113aa2e36cd`	completed	May 21, 2026, 11:41 p.m.
PD	Predicate disambiguation	`batch_69f17651458c8190bbfd301883e46085`	completed	April 29, 2026, 3:09 a.m.

Created at: April 17, 2026, 11:04 p.m.