Triple

T26094352

Position	Surface form	Disambiguated ID	Type / Status
Subject	Tallangatta	`E658218`	entity
Predicate	hasSecondaryCollege	`P146206`	FINISHED
Object	Tallangatta Secondary College Tallangatta Secondary College is a public secondary school serving students from the town of Tallangatta and surrounding rural communities in Victoria, Australia.	`E1710068`	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: Tallangatta Secondary College | Statement: [Tallangatta, hasSecondaryCollege, Tallangatta Secondary College]

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: Tallangatta Secondary College
Triple: [Tallangatta, hasSecondaryCollege, Tallangatta Secondary College]

Generated description

Tallangatta Secondary College is a public secondary school serving students from the town of Tallangatta and surrounding rural communities in Victoria, Australia.

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

Target predicate: hasSecondaryCollege
Context triple: [Tallangatta, hasSecondaryCollege, Tallangatta Secondary College]

A. hasCollegeType
Indicates that a college or educational institution is classified as having a specific type or category (e.g., public, private, community, technical).
B. hasSecondarySchoolLevel
Indicates that an entity possesses or is associated with a level of education corresponding to secondary school.
C. hasAdjacentCollege
Indicates that one entity has a college located directly next to or bordering it.
D. hasFurtherEducationInstitution chosen
Indicates that an entity is associated with, or has access to, a further education institution (such as a college or post-secondary training provider).
E. hasJuniorCollege
Indicates that an entity operates, is associated with, or includes a junior college as part of its structure or offerings.
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_69ee5bbfc4d08190a1b206d0ac3a1e8d`	completed	April 26, 2026, 6:38 p.m.
NER	Named-entity recognition	`batch_69f73223675481908c1bc3208c0f5284`	completed	May 3, 2026, 11:31 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a11274ac0608190a601b3211ebc6e1e`	completed	May 23, 2026, 4:04 a.m.
NEDg	Description generation	`batch_6a1137d8159481909e2d22656e83b9f2`	completed	May 23, 2026, 5:15 a.m.
NED2	Entity disambiguation (via description)	`batch_6a11394a2d6081908a6083f02acd555d`	completed	May 23, 2026, 5:21 a.m.
PD	Predicate disambiguation	`batch_69f7317690108190b3aae2cd2e1d069e`	completed	May 3, 2026, 11:28 a.m.

Created at: April 26, 2026, 7:50 p.m.