Triple

T21011769
Position Surface form Disambiguated ID Type / Status
Subject Cettiidae E517566 entity
Predicate includes P1393 FINISHED
Object Tesia
Tesia is a genus of small, ground-dwelling Old World warblers known for their short tails and secretive behavior in dense undergrowth.
 E1462777 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: Tesia | Statement: [Cettiidae, includes, Tesia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tesia
Context triple: [Cettiidae, includes, Tesia]
  • A. Tenea
    Tenea was an ancient Greek city, traditionally associated with Corinthian colonists and mythic Trojan origins, known from classical sources and archaeological discoveries in the Peloponnese.
  • B. Terina
    Terina was an ancient Greek-founded city in southern Italy’s Bruttium region, known as a significant coastal and commercial center in Magna Graecia.
  • C. Turnesa
    Turnesa is the surname of a prominent American golfing family that produced several notable professional golfers in the early to mid-20th century.
  • D. Tianeti
    Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
  • E. Atessa
    Atessa is a town and municipality in the Abruzzo region of central Italy, known for its industrial activity and automotive manufacturing 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: Tesia
Triple: [Cettiidae, includes, Tesia]
Generated description
Tesia is a genus of small, ground-dwelling Old World warblers known for their short tails and secretive behavior in dense undergrowth.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tesia
Target entity description: Tesia is a genus of small, ground-dwelling Old World warblers known for their short tails and secretive behavior in dense undergrowth.
  • A. Tenea
    Tenea was an ancient Greek city, traditionally associated with Corinthian colonists and mythic Trojan origins, known from classical sources and archaeological discoveries in the Peloponnese.
  • B. Terina
    Terina was an ancient Greek-founded city in southern Italy’s Bruttium region, known as a significant coastal and commercial center in Magna Graecia.
  • C. Turnesa
    Turnesa is the surname of a prominent American golfing family that produced several notable professional golfers in the early to mid-20th century.
  • D. Tianeti
    Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
  • E. Atessa
    Atessa is a town and municipality in the Abruzzo region of central Italy, known for its industrial activity and automotive manufacturing 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_69e0b50192308190a284fcc89dd23a49 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc40f91c81908c9b6d99869de7aa completed April 21, 2026, 4:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a093b60b94081909bea5b8b0cf81447 completed May 17, 2026, 3:52 a.m.
NEDg Description generation batch_6a093d500adc8190ba08e8a6c1674563 completed May 17, 2026, 4 a.m.
NED2 Entity disambiguation (via description) batch_6a093e445e748190a20721d0718c71bc completed May 17, 2026, 4:04 a.m.
Created at: April 16, 2026, 1:53 p.m.