Triple

T867331
Position Surface form Disambiguated ID Type / Status
Subject Porai Mata E18732 entity
Predicate hasTitle P38 FINISHED
Object Mata
Mata is a title used in certain South Asian cultural and religious contexts, often signifying a revered mother figure or goddess.
 E100841 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: Mata | Statement: [Porai Mata, hasTitle, Mata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mata
Context triple: [Porai Mata, hasTitle, Mata]
  • A. Mikuma
    Mikuma was a Japanese Mogami-class heavy cruiser of the Imperial Japanese Navy that served in World War II and was sunk during the Battle of Midway.
  • B. Mewar
    Mewar is a historic region in northwestern India known for its Rajput heritage, hill forts, and former princely state centered around Udaipur.
  • C. Tama
    Tama is a region in western Tokyo, Japan, encompassing several suburban cities and towns that serve as residential and commercial areas for the greater Tokyo metropolis.
  • D. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • E. Kiko
    Kiko is the young, albino giant ape who serves as the gentle offspring and companion of King Kong in the 1933 film "Son of Kong."
  • 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: Mata
Triple: [Porai Mata, hasTitle, Mata]
Generated description
Mata is a title used in certain South Asian cultural and religious contexts, often signifying a revered mother figure or goddess.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mata
Target entity description: Mata is a title used in certain South Asian cultural and religious contexts, often signifying a revered mother figure or goddess.
  • A. Mikuma
    Mikuma was a Japanese Mogami-class heavy cruiser of the Imperial Japanese Navy that served in World War II and was sunk during the Battle of Midway.
  • B. Mewar
    Mewar is a historic region in northwestern India known for its Rajput heritage, hill forts, and former princely state centered around Udaipur.
  • C. Tama
    Tama is a region in western Tokyo, Japan, encompassing several suburban cities and towns that serve as residential and commercial areas for the greater Tokyo metropolis.
  • D. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • E. Kiko
    Kiko is the young, albino giant ape who serves as the gentle offspring and companion of King Kong in the 1933 film "Son of Kong."
  • 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_69a4938ce8688190a24bdfef82ba7d21 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac7e12b0819084d25b9a66888a91 completed March 1, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3c9e7ec819081d58634fe0efdcb completed March 4, 2026, 3:15 a.m.
NEDg Description generation batch_69a7a44c2d5881909d006ddf9f9ed694 completed March 4, 2026, 3:17 a.m.
NED2 Entity disambiguation (via description) batch_69a7a4a811bc819093bd436de45afa97 completed March 4, 2026, 3:19 a.m.
Created at: March 1, 2026, 7:39 p.m.