Triple

T34701651

Position	Surface form	Disambiguated ID	Type / Status
Subject	Parks Road, Oxford	`E1000385`	entity
Predicate	hasLandmarkAtJunction	`P184542`	FINISHED
Object	King’s Arms public house King’s Arms public house is a historic and popular Oxford pub near the university, known as a longstanding meeting place for students, academics, and visitors.	`E2108301`	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: King’s Arms public house | Statement: [Parks Road, Oxford, hasLandmarkAtJunction, King’s Arms public house]

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: King’s Arms public house
Triple: [Parks Road, Oxford, hasLandmarkAtJunction, King’s Arms public house]

Generated description

King’s Arms public house is a historic and popular Oxford pub near the university, known as a longstanding meeting place for students, academics, and visitors.

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

Target predicate: hasLandmarkAtJunction
Context triple: [Parks Road, Oxford, hasLandmarkAtJunction, King’s Arms public house]

A. atJunctionOf chosen
Indicates that something is located at or directly connected to the point where two or more paths, roads, or lines meet.
B. trailJunctionOf
Indicates that one trail serves as a junction or connecting point between two or more other trails.
C. nearJunctionOf
Indicates that one entity is located close to the point where two or more linear features (such as roads, tracks, or paths) meet or intersect.
D. isMajorRoadJunction
Indicates that a location serves as a primary intersection where major roads or highways meet or cross.
E. hasJunctionWith
Indicates that one entity meets or intersects with another at a shared junction point.
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_69f76dab937881909c86f1b9ad50445f`	completed	May 3, 2026, 3:45 p.m.
NER	Named-entity recognition	`batch_69ff4de66ba481908e7184b3cf9d4d2d`	completed	May 9, 2026, 3:08 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a37530598488190b7de90e35623cb37`	completed	June 21, 2026, 2:57 a.m.
NEDg	Description generation	`batch_6a3754b1aae4819099e384db390b6e31`	completed	June 21, 2026, 3:04 a.m.
NED2	Entity disambiguation (via description)	`batch_6a3755355350819087aa38073ff6f67a`	completed	June 21, 2026, 3:06 a.m.
PD	Predicate disambiguation	`batch_69ff4c702a5881909c6684c74807e945`	completed	May 9, 2026, 3:02 p.m.

Created at: May 3, 2026, 3:59 p.m.