Triple

T23991328

Position	Surface form	Disambiguated ID	Type / Status
Subject	Baseline station	`E605073`	entity
Predicate	adjacentStationOnTransitway	`P154534`	FINISHED
Object	Iris station Iris station is a transitway station in Ottawa, Ontario, serving as a stop on the city’s bus rapid transit and light rail network.	`E1613582`	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: Iris station | Statement: [Baseline station, adjacentStationOnTransitway, Iris station]

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: Iris station
Triple: [Baseline station, adjacentStationOnTransitway, Iris station]

Generated description

Iris station is a transitway station in Ottawa, Ontario, serving as a stop on the city’s bus rapid transit and light rail network.

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

Target predicate: adjacentStationOnTransitway
Context triple: [Baseline station, adjacentStationOnTransitway, Iris station]

A. adjacentStationOnLine
Indicates that one station is directly next to another station along the same transit line, with no other station in between.
B. adjacentToStation
Indicates that one entity is located next to or immediately beside a station.
C. adjacentStationOnLine2
Indicates that one station is directly next to another station along line 2 in a transit or rail network.
D. adjacentStationOnLineD
Indicates that one station is directly next to another station along line D, with no other stations in between on that line.
E. adjacentStationOnMetropolitanLine
Indicates that one station is directly next to another station along the Metropolitan Line, with no other stations in between on that line.
F. None of above. chosen

Provenance (7 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_69e295463f7c8190b1c19dbd114641b9`	completed	April 17, 2026, 8:17 p.m.
NER	Named-entity recognition	`batch_69f1d38c28d48190937660529bbced19`	completed	April 29, 2026, 9:46 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a0f7e8e7b288190a33fed8a5eadbcbc`	completed	May 21, 2026, 9:52 p.m.
NEDg	Description generation	`batch_6a0f7f6e3808819084a560d1a0048882`	completed	May 21, 2026, 9:55 p.m.
NED2	Entity disambiguation (via description)	`batch_6a0f801244d08190b9403a8a7bfe520e`	completed	May 21, 2026, 9:58 p.m.
PD	Predicate disambiguation	`batch_69f1615994c48190a5de95d3f7e5cd0a`	completed	April 29, 2026, 1:39 a.m.
PDg	Predicate description generation	`batch_69f16e348b548190b76e50f9b611f76d`	completed	April 29, 2026, 2:34 a.m.

Created at: April 17, 2026, 9:37 p.m.