Triple

T18350070
Position Surface form Disambiguated ID Type / Status
Subject canton of Muret E439641 entity
Predicate contains P35 FINISHED
Object Lherm
Lherm is a small commune in southwestern France, located in the Haute-Garonne department near the city of Toulouse.
 E1319627 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: Lherm | Statement: [canton of Muret, contains, Lherm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lherm
Context triple: [canton of Muret, contains, Lherm]
  • A. Montagnieu
    Montagnieu is a commune in the Ain department of eastern France, situated within the historic wine-producing area of Bugey.
  • B. Mourtemeno
    Mourtemeno is a small Greek island located off the coast of Syvota in the Ionian Sea, known for its clear waters and scenic coves.
  • C. Lemerig
    Lemerig is an endangered Oceanic language spoken by a small community on the island of Vanua Lava in northern Vanuatu.
  • D. Gressy
    Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
  • E. Lepechin
    Lepechin was an 18th-century Russian naturalist and explorer known for his extensive zoological and botanical studies across the Russian Empire.
  • 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: Lherm
Triple: [canton of Muret, contains, Lherm]
Generated description
Lherm is a small commune in southwestern France, located in the Haute-Garonne department near the city of Toulouse.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lherm
Target entity description: Lherm is a small commune in southwestern France, located in the Haute-Garonne department near the city of Toulouse.
  • A. Montagnieu
    Montagnieu is a commune in the Ain department of eastern France, situated within the historic wine-producing area of Bugey.
  • B. Mourtemeno
    Mourtemeno is a small Greek island located off the coast of Syvota in the Ionian Sea, known for its clear waters and scenic coves.
  • C. Lemerig
    Lemerig is an endangered Oceanic language spoken by a small community on the island of Vanua Lava in northern Vanuatu.
  • D. Gressy
    Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
  • E. Lepechin
    Lepechin was an 18th-century Russian naturalist and explorer known for his extensive zoological and botanical studies across the Russian Empire.
  • 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_69d8b918221c8190a9f7b563d64ac677 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e514f7700c8190ae220de870e69304 completed April 19, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03cc28b80c8190819b989478bb62bd completed May 13, 2026, 12:56 a.m.
NEDg Description generation batch_6a03cd1858c481909f78fb1a4c27437c completed May 13, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_6a03ce9e3dd08190b912fe9e9f552053 completed May 13, 2026, 1:06 a.m.
Created at: April 10, 2026, 10:37 a.m.