Triple

T11868179
Position Surface form Disambiguated ID Type / Status
Subject Teresa Ganzel E282337 entity
Predicate givenName P17 FINISHED
Object Teresa
Teresa is a feminine given name of Greek origin meaning "harvester" or "reaper," borne by numerous notable women across history and popular culture.
 E553842 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: [Teresa Ganzel, givenName, Teresa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Teresa
Context triple: [Teresa Ganzel, givenName, Teresa]
  • A. Teresa
    Teresa is the central protagonist of the play "The Memory of Water," around whom the story’s emotional and familial conflicts revolve.
  • B. 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.
  • C. Teresa
    Teresa is a Mexican telenovela that helped launch Salma Hayek to fame through her lead role as an ambitious, morally conflicted young woman.
  • D. 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.
  • E. Teresa
    Teresa is a municipality in the province of Rizal in the Philippines, known for its residential communities and proximity to Metro Manila.
  • 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: [Teresa Ganzel, givenName, Teresa]
Generated description
Teresa is a feminine given name of Greek origin meaning "harvester" or "reaper," borne by numerous notable women across history and popular culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Teresa
Target entity description: Teresa is a feminine given name of Greek origin meaning "harvester" or "reaper," borne by numerous notable women across history and popular culture.
  • A. Teresa chosen
    Teresa is a feminine given name commonly used in various cultures, often associated with notable religious and historical figures.
  • B. 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.
  • C. Teresa
    Teresa is the middle name of Tamar Teresa Day Hennessy.
  • D. Teresa
    Teresa is a Mexican telenovela that helped launch Salma Hayek to fame through her lead role as an ambitious, morally conflicted young woman.
  • E. Teresa
    Teresa is the central protagonist of the play "The Memory of Water," around whom the story’s emotional and familial conflicts revolve.
  • F. None of above.

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_69d6ab2945d081908a5851c916cbcfb5 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a73c04e4819084c0b2ff8e5d2f04 completed April 10, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69f417bb131c8190b0923e077cca74be completed May 1, 2026, 3:02 a.m.
NEDg Description generation batch_69f41f8d297c81908cfe60b10989e550 completed May 1, 2026, 3:35 a.m.
NED2 Entity disambiguation (via description) batch_69f422778a10819093bc2473ef30fe71 completed May 1, 2026, 3:48 a.m.
Created at: April 8, 2026, 9:43 p.m.