Triple

T31143283

Position	Surface form	Disambiguated ID	Type / Status
Subject	Book of Leinster	`E793848`	entity
Predicate	shelfMark	`P20097`	FINISHED
Object	TCD MS 1339 TCD MS 1339 is the medieval Irish manuscript held at Trinity College Dublin that is commonly known as the Book of Leinster.	`E1947112`	NE FINISHED

How this triple was built (2 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: TCD MS 1339 | Statement: [Book of Leinster, shelfMark, TCD MS 1339]

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: TCD MS 1339
Triple: [Book of Leinster, shelfMark, TCD MS 1339]

Generated description

TCD MS 1339 is the medieval Irish manuscript held at Trinity College Dublin that is commonly known as the Book of Leinster.

Provenance (5 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_69f224d2b3a48190aa9dd26fbf6eab1a`	completed	April 29, 2026, 3:33 p.m.
NER	Named-entity recognition	`batch_69f697974e4c819090a4e708a25055d8`	completed	May 3, 2026, 12:32 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a2938cf8ff08190a83b5782e39ca8eb`	completed	June 10, 2026, 10:13 a.m.
NEDg	Description generation	`batch_6a2939db5768819087ecea8a785c637d`	completed	June 10, 2026, 10:18 a.m.
NED2	Entity disambiguation (via description)	`batch_6a293bf644548190beb05576e2c10d29`	completed	June 10, 2026, 10:27 a.m.

Created at: April 29, 2026, 9:06 p.m.