Triple

T19938795
Position Surface form Disambiguated ID Type / Status
Subject Rue du Faubourg-Saint-Antoine E479246 entity
Predicate hasPart P35 FINISHED
Object Cour de la Forge
Cour de la Forge is a historic inner courtyard in Paris known for its traditional artisan workshops and preserved 19th-century atmosphere.
 E1403334 NE FINISHED

How this triple was built (4 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: Cour de la Forge | Statement: [Rue du Faubourg-Saint-Antoine, hasPart, Cour de la Forge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cour de la Forge
Context triple: [Rue du Faubourg-Saint-Antoine, hasPart, Cour de la Forge]
  • A. Surpierre
    Surpierre is a small municipality in the canton of Fribourg in western Switzerland.
  • B. La Garde-Freinet
    La Garde-Freinet is a picturesque Provençal village in southeastern France, known for its historic hilltop setting, chestnut forests, and views over the Gulf of Saint-Tropez.
  • C. Lalumière
    Lalumière is a French surname most notably borne by Catherine Lalumière, a prominent French politician and former European Parliament member.
  • D. Porte d’Orée
    Porte d’Orée is a historic Roman-era gate in Fréjus, France, notable as a remnant of the ancient city’s fortifications.
  • E. Gagnière
    Gagnière is a French surname, likely of regional origin, associated with individuals such as Mahoudeau.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Cour de la Forge
Triple: [Rue du Faubourg-Saint-Antoine, hasPart, Cour de la Forge]
Generated description
Cour de la Forge is a historic inner courtyard in Paris known for its traditional artisan workshops and preserved 19th-century atmosphere.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cour de la Forge
Target entity description: Cour de la Forge is a historic inner courtyard in Paris known for its traditional artisan workshops and preserved 19th-century atmosphere.
  • A. Surpierre
    Surpierre is a small municipality in the canton of Fribourg in western Switzerland.
  • B. La Garde-Freinet
    La Garde-Freinet is a picturesque Provençal village in southeastern France, known for its historic hilltop setting, chestnut forests, and views over the Gulf of Saint-Tropez.
  • C. Lalumière
    Lalumière is a French surname most notably borne by Catherine Lalumière, a prominent French politician and former European Parliament member.
  • D. Porte d’Orée
    Porte d’Orée is a historic Roman-era gate in Fréjus, France, notable as a remnant of the ancient city’s fortifications.
  • E. Gagnière
    Gagnière is a French surname, likely of regional origin, associated with individuals such as Mahoudeau.
  • F. None of above. chosen

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_69d8e522a17c819095165d4d24939fd8 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65a190ac08190b9dc7955c9764a71 completed April 20, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07f6ec40f88190926f1330300fdc61 completed May 16, 2026, 4:47 a.m.
NEDg Description generation batch_6a07f9c8f6c08190a949ebbb70b08d01 completed May 16, 2026, 4:59 a.m.
NED2 Entity disambiguation (via description) batch_6a07fb3a144c8190b9bf2148702d6b6c completed May 16, 2026, 5:06 a.m.
Created at: April 10, 2026, 1:53 p.m.