Triple

T9820702
Position Surface form Disambiguated ID Type / Status
Subject Loiret department E238522 entity
Predicate hasCity P316 FINISHED
Object Saran
Saran is a commune in north-central France located in the Loiret department, near the city of Orléans.
 E823839 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: Saran | Statement: [Loiret department, hasCity, Saran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Saran
Context triple: [Loiret department, hasCity, Saran]
  • A. Sar
    Sar is the family name of Pol Pot, the Cambodian revolutionary leader and dictator who headed the Khmer Rouge regime responsible for the Cambodian genocide.
  • B. Sarju
    Sarju is an alternate name for the Sarayu, a river historically associated with the ancient Indian city of Ayodhya and revered in Hindu tradition.
  • C. Sanaig
    Sanaig is a core single malt Scotch whisky expression from Islay’s Kilchoman distillery, known for its balance of bourbon and sherry cask influence with a characteristically smoky, coastal profile.
  • D. Caron
    Caron is a French surname most famously associated with actress and dancer Leslie Caron, known for her roles in classic Hollywood musicals.
  • E. Nonsan
    Nonsan is a city in South Chungcheong Province, South Korea, known for its agricultural production and military training facilities.
  • 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: Saran
Triple: [Loiret department, hasCity, Saran]
Generated description
Saran is a commune in north-central France located in the Loiret department, near the city of Orléans.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Saran
Target entity description: Saran is a commune in north-central France located in the Loiret department, near the city of Orléans.
  • A. Sar
    Sar is the family name of Pol Pot, the Cambodian revolutionary leader and dictator who headed the Khmer Rouge regime responsible for the Cambodian genocide.
  • B. Sarju
    Sarju is an alternate name for the Sarayu, a river historically associated with the ancient Indian city of Ayodhya and revered in Hindu tradition.
  • C. Sanaig
    Sanaig is a core single malt Scotch whisky expression from Islay’s Kilchoman distillery, known for its balance of bourbon and sherry cask influence with a characteristically smoky, coastal profile.
  • D. Caron
    Caron is a French surname most famously associated with actress and dancer Leslie Caron, known for her roles in classic Hollywood musicals.
  • E. Nonsan
    Nonsan is a city in South Chungcheong Province, South Korea, known for its agricultural production and military training facilities.
  • 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb313134081908eb0ba3a22b22e2b completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc78ffcc8190bb26a224350376dc completed April 5, 2026, 2:44 a.m.
NEDg Description generation batch_69d1cd8e7c548190bc3f10004db80925 completed April 5, 2026, 2:48 a.m.
NED2 Entity disambiguation (via description) batch_69d1ce1aead081908da4a85ded350c17 completed April 5, 2026, 2:51 a.m.
Created at: March 30, 2026, 8:31 p.m.