Triple

T4515493
Position Surface form Disambiguated ID Type / Status
Subject Tamar Teresa Day Hennessy E102143 entity
Predicate middleName P143 FINISHED
Object Teresa
Teresa is the middle name of Tamar Teresa Day Hennessy.
 E448955 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: Teresa | Statement: [Tamar Teresa Day Hennessy, middleName, Teresa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Teresa
Context triple: [Tamar Teresa Day Hennessy, middleName, Teresa]
  • A. Teresa
    Teresa is a Mexican telenovela that helped launch Salma Hayek to fame through her lead role as an ambitious, morally conflicted young woman.
  • B. Teresa
    Teresa is a central figure in Carlos Fuentes’s novel "The Death of Artemio Cruz," representing both a pivotal love interest and a symbol of the social and emotional conflicts surrounding the protagonist.
  • C. Teresa
    Teresa is the religious name of Mother Teresa, the Catholic nun and missionary renowned for her charitable work with the poor in Kolkata, India.
  • D. Teressa
    Teressa is a Nicobarese language variety spoken by the indigenous community on Teressa Island in India’s Nicobar archipelago.
  • E. Santa Teresa Cora
    Santa Teresa Cora is a regional dialect of the Cora language spoken by the indigenous Cora people of western Mexico.
  • 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: Teresa
Triple: [Tamar Teresa Day Hennessy, middleName, Teresa]
Generated description
Teresa is the middle name of Tamar Teresa Day Hennessy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Teresa
Target entity description: Teresa is the middle name of Tamar Teresa Day Hennessy.
  • A. Teresa
    Teresa is the religious name of Mother Teresa, the Catholic nun and missionary renowned for her charitable work with the poor in Kolkata, India.
  • B. Teresa
    Teresa is a Mexican telenovela that helped launch Salma Hayek to fame through her lead role as an ambitious, morally conflicted young woman.
  • C. Teresa
    Teresa is a central figure in Carlos Fuentes’s novel "The Death of Artemio Cruz," representing both a pivotal love interest and a symbol of the social and emotional conflicts surrounding the protagonist.
  • D. Teressa
    Teressa is a Nicobarese language variety spoken by the indigenous community on Teressa Island in India’s Nicobar archipelago.
  • E. Santa Teresa Cora
    Santa Teresa Cora is a regional dialect of the Cora language spoken by the indigenous Cora people of western Mexico.
  • 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_69bd43d6251c81909deecce3e6e9d69c completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5725745c81908bb462ba9537ae14 completed March 20, 2026, 2:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd7f8f66ac8190b719a653686c7258 completed March 20, 2026, 5:10 p.m.
NEDg Description generation batch_69bd803a225c8190ab82d0e36c9ff3f5 completed March 20, 2026, 5:13 p.m.
NED2 Entity disambiguation (via description) batch_69bd84c11d8881908819b36669dee7b5 completed March 20, 2026, 5:32 p.m.
Created at: March 20, 2026, 1:02 p.m.