Triple

T34514368

Position	Surface form	Disambiguated ID	Type / Status
Subject	Green Line (Luas)	`E886107`	entity
Predicate	formerUseOfAlignment	`P201626`	FINISHED
Object	Harcourt Street railway line The Harcourt Street railway line was a former suburban rail route in Dublin, Ireland, whose disused alignment later formed the basis for much of the modern Luas Green Line.	`E2101096`	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: Harcourt Street railway line | Statement: [Green Line (Luas), formerUseOfAlignment, Harcourt Street railway line]

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: Harcourt Street railway line
Triple: [Green Line (Luas), formerUseOfAlignment, Harcourt Street railway line]

Generated description

The Harcourt Street railway line was a former suburban rail route in Dublin, Ireland, whose disused alignment later formed the basis for much of the modern Luas Green Line.

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

Target predicate: formerUseOfAlignment
Context triple: [Green Line (Luas), formerUseOfAlignment, Harcourt Street railway line]

A. usedByAlignment
Indicates that something is utilized or applied by a particular alignment, orientation, or positioning configuration.
B. alignmentUsage
Indicates how an entity’s alignment, orientation, or positioning is applied or utilized in relation to another entity or context.
C. previousAlignment
Indicates that one entity’s alignment or orientation occurred earlier in time than another’s.
D. originallyAlignedWith
Indicates that an entity was initially in agreement, support, or association with another entity or group, regardless of any later changes in stance or affiliation.
E. historicalAlignmentOf
Indicates a relationship where entities share or are compared based on their positions, roles, or associations within a specific historical context or period.
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_69f349ccc290819089d8e82698e53cb6`	completed	April 30, 2026, 12:23 p.m.
NER	Named-entity recognition	`batch_6a000efe971081909de03f875a7ad6cc`	completed	May 10, 2026, 4:52 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a3729df87508190a6a8141361169713`	completed	June 21, 2026, 12:01 a.m.
NEDg	Description generation	`batch_6a372a9fffa481909279c5fd09903e91`	completed	June 21, 2026, 12:04 a.m.
NED2	Entity disambiguation (via description)	`batch_6a372b3eb16c8190bd4546837763231c`	completed	June 21, 2026, 12:07 a.m.
PD	Predicate disambiguation	`batch_6a000c4ffe788190a5757af60aadd9f3`	completed	May 10, 2026, 4:40 a.m.
PDg	Predicate description generation	`batch_6a000efdbe948190b4bfa9871aa1a7ee`	completed	May 10, 2026, 4:52 a.m.

Created at: May 1, 2026, 2:01 a.m.