Triple

T2476882
Position Surface form Disambiguated ID Type / Status
Subject Lake Annecy E55108 entity
Predicate outflow P967 FINISHED
Object Thiou
Thiou is a short river in southeastern France that drains Lake Annecy and flows through the old town of Annecy.
 E269838 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: Thiou | Statement: [Lake Annecy, outflow, Thiou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Thiou
Context triple: [Lake Annecy, outflow, Thiou]
  • A. Thann
    Thann is a small historic town in northeastern France, located at the foot of the Vosges mountains in the Haut-Rhin department of Alsace.
  • B. Thyone
    Thyone is the deified name of Semele, the mortal mother of Dionysus in Greek mythology who was later worshipped as a goddess.
  • C. Terik
    Terik is a Southern Nilotic language spoken by the Terik people of western Kenya, closely related to Nandi and other Kalenjin languages.
  • D. Tianeti
    Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
  • E. Thout
    Thout is the first month of the Coptic calendar, traditionally marking the beginning of the Coptic year and associated with the ancient Egyptian god Thoth.
  • 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: Thiou
Triple: [Lake Annecy, outflow, Thiou]
Generated description
Thiou is a short river in southeastern France that drains Lake Annecy and flows through the old town of Annecy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Thiou
Target entity description: Thiou is a short river in southeastern France that drains Lake Annecy and flows through the old town of Annecy.
  • A. Thann
    Thann is a small historic town in northeastern France, located at the foot of the Vosges mountains in the Haut-Rhin department of Alsace.
  • B. Thyone
    Thyone is the deified name of Semele, the mortal mother of Dionysus in Greek mythology who was later worshipped as a goddess.
  • C. Terik
    Terik is a Southern Nilotic language spoken by the Terik people of western Kenya, closely related to Nandi and other Kalenjin languages.
  • D. Tianeti
    Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
  • E. Thout
    Thout is the first month of the Coptic calendar, traditionally marking the beginning of the Coptic year and associated with the ancient Egyptian god Thoth.
  • 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_69ab49e279e88190ab10d7248aea9d11 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd14dde208190ad4e1c9de5d43b0a completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17aea398819092cb14b93abd0ff7 completed March 9, 2026, 6:55 p.m.
NEDg Description generation batch_69af18f9af388190bbb4242c89d4272e completed March 9, 2026, 7:01 p.m.
NED2 Entity disambiguation (via description) batch_69af198534c0819090c742f39501fac6 completed March 9, 2026, 7:03 p.m.
Created at: March 6, 2026, 9:45 p.m.