Triple

T36217280

Position	Surface form	Disambiguated ID	Type / Status
Subject	Directoire français	`E1047732`	entity
Predicate	monnaie	`P245`	FINISHED
Object	livre tournois The livre tournois was the principal unit of account and currency in France from the Middle Ages until its replacement by the franc during the French Revolution.	`E1785487`	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: livre tournois | Statement: [Directoire français, monnaie, livre tournois]

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: livre tournois
Triple: [Directoire français, monnaie, livre tournois]

Generated description

The livre tournois was the principal unit of account and currency in France from the Middle Ages until its replacement by the franc during the French Revolution.

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

Target predicate: monnaie
Context triple: [Directoire français, monnaie, livre tournois]

A. currency chosen
Indicates that one entity serves as the medium of exchange or monetary unit used by another entity (such as a country, region, or system).
B. currencyDepicted
Indicates that one entity visually represents or shows the image or symbol of a particular currency on it.
C. currencyProduced
Indicates that an entity is responsible for creating, issuing, or generating a particular form of currency.
D. coinageType
Indicates the specific type or category of coinage associated with an entity, such as its denomination, series, or monetary classification.
E. mediumOfCoinage
Indicates the material or substance used as the physical medium in which a coin or form of money is produced.
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_69f76e42c878819095c8d19c0267fb87`	completed	May 3, 2026, 3:48 p.m.
NER	Named-entity recognition	`batch_69f7b57e4d788190b8dbcb178a0fe285`	completed	May 3, 2026, 8:52 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a3934297a34819092323eb7670e031f`	completed	June 22, 2026, 1:10 p.m.
NEDg	Description generation	`batch_6a39375c4f008190aeaf18ba8d062682`	completed	June 22, 2026, 1:23 p.m.
NED2	Entity disambiguation (via description)	`batch_6a39380694148190baccad938fee0c4f`	completed	June 22, 2026, 1:26 p.m.
PD	Predicate disambiguation	`batch_69f7b4c44390819084fb5558b354658f`	completed	May 3, 2026, 8:49 p.m.

Created at: May 3, 2026, 4:09 p.m.