Triple

T25813621

Position	Surface form	Disambiguated ID	Type / Status
Subject	Robert Miles Infant School	`E650187`	entity
Predicate	hasNeighbouringSchool	`P6776`	FINISHED
Object	Robert Miles Junior School Robert Miles Junior School is a primary education institution that serves older children in the same local community as Robert Miles Infant School.	`E650187`	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: Robert Miles Junior School | Statement: [Robert Miles Infant School, hasNeighbouringSchool, Robert Miles Junior School]

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: Robert Miles Junior School
Triple: [Robert Miles Infant School, hasNeighbouringSchool, Robert Miles Junior School]

Generated description

Robert Miles Junior School is a primary education institution that serves older children in the same local community as Robert Miles Infant School.

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

Target predicate: hasNeighbouringSchool
Context triple: [Robert Miles Infant School, hasNeighbouringSchool, Robert Miles Junior School]

A. hasNearbyInstitution chosen
Indicates that one entity is located close to or in the immediate vicinity of an institution.
B. hasSchoolIn
Indicates that a school is located within or operates in a specified place or region.
C. hasNearbyInstitutionType
Indicates that an entity has at least one institution of a specified type located in its nearby geographic vicinity.
D. sharesRegionalSchoolDistrictWith
Indicates that two entities are part of, or served by, the same regional school district.
E. hasRegionalSchool
Indicates that an entity has an associated school that serves or operates within a specific geographic region.
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_69e7ab35d264819095367f7e80c983ff`	completed	April 21, 2026, 4:52 p.m.
NER	Named-entity recognition	`batch_69f6c49627908190b3553474c7c3072b`	completed	May 3, 2026, 3:44 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a10da1d33888190a462e23f7c9bbe57`	completed	May 22, 2026, 10:35 p.m.
NEDg	Description generation	`batch_6a10db095b9481909821c75de861c625`	completed	May 22, 2026, 10:39 p.m.
NED2	Entity disambiguation (via description)	`batch_6a10dc8daac48190af6df901b02fcd00`	completed	May 22, 2026, 10:45 p.m.
PD	Predicate disambiguation	`batch_69f6c3f23ae081909a52801266063a3c`	completed	May 3, 2026, 3:41 a.m.

Created at: April 22, 2026, 7:12 a.m.