Triple

T5873523
Position Surface form Disambiguated ID Type / Status
Subject Orange (city) E130572 entity
Predicate demonym P191 FINISHED
Object Orangeoises
Orangeoises are the inhabitants of the French city of Orange, located in the Vaucluse department in southeastern France.
 E553873 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: Orangeoises | Statement: [Orange (city), demonym, Orangeoises]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Orangeoises
Context triple: [Orange (city), demonym, Orangeoises]
  • A. Orcines
    Orcines is a commune in central France’s Puy-de-Dôme department, known for its proximity to the Chaîne des Puys volcanic range.
  • B. Loro
    Loro is an Italian biographical drama film directed by Paolo Sorrentino that portrays the controversial life and political milieu surrounding former Prime Minister Silvio Berlusconi.
  • C. Grolleau
    Grolleau is a French red grape variety primarily used to produce light, fruity rosé and red wines, especially in the Anjou region.
  • D. Monrupino
    Monrupino is a small municipality in northeastern Italy near the Slovenian border, known for its Karst landscape and bilingual Italian-Slovene cultural heritage.
  • E. Donder
    Donder is one of Santa Claus’s traditional reindeer, often listed alongside Dancer and the other members of his Christmas sleigh team.
  • 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: Orangeoises
Triple: [Orange (city), demonym, Orangeoises]
Generated description
Orangeoises are the inhabitants of the French city of Orange, located in the Vaucluse department in southeastern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Orangeoises
Target entity description: Orangeoises are the inhabitants of the French city of Orange, located in the Vaucluse department in southeastern France.
  • A. Orcines
    Orcines is a commune in central France’s Puy-de-Dôme department, known for its proximity to the Chaîne des Puys volcanic range.
  • B. Loro
    Loro is an Italian biographical drama film directed by Paolo Sorrentino that portrays the controversial life and political milieu surrounding former Prime Minister Silvio Berlusconi.
  • C. Grolleau
    Grolleau is a French red grape variety primarily used to produce light, fruity rosé and red wines, especially in the Anjou region.
  • D. Monrupino
    Monrupino is a small municipality in northeastern Italy near the Slovenian border, known for its Karst landscape and bilingual Italian-Slovene cultural heritage.
  • E. Donder
    Donder is one of Santa Claus’s traditional reindeer, often listed alongside Dancer and the other members of his Christmas sleigh team.
  • 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_69c0085047dc8190af24e311edad3c07 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c035fafb54819085378e7c8d137402 completed March 22, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b11b48d88190ba6cd5ade2f47a89 completed March 23, 2026, 3:18 a.m.
NEDg Description generation batch_69c0b1cb731481909de9c3fde3595b7b completed March 23, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_69c0b27f53608190b2a1f78e3cd1b634 completed March 23, 2026, 3:24 a.m.
Created at: March 22, 2026, 3:57 p.m.