Triple

T10765730
Position Surface form Disambiguated ID Type / Status
Subject Alice campus E253948 entity
Predicate locatedInSettlement P21214 FINISHED
Object Alice
Alice is a small town in the Eastern Cape province of South Africa, known for its university campus and historical significance.
E877316 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: Alice | Statement: [Alice campus, locatedInSettlement, Alice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alice
Context triple: [Alice campus, locatedInSettlement, Alice]
  • A. Alice
    Alice is the curious young girl who serves as the main protagonist of Disney’s animated film "Alice in Wonderland."
  • B. Alice
    Alice is a Direct Memory Access (DMA) controller used in Commodore's Amiga AGA chipset generation to handle high-speed data transfers between memory and peripherals.
  • C. Alice
    Alice is an American sitcom that aired from the mid-1970s to the mid-1980s, following a widowed waitress working at a roadside diner and the quirky people in her life.
  • D. Alice
    Alice is an ultraviolet imaging spectrograph aboard NASA's New Horizons spacecraft, used to study the composition and structure of planetary atmospheres and surfaces.
  • E. Alice
    Alice is the conventional placeholder name used to represent a generic sender or participant in cryptographic protocols and security examples.
  • 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: Alice
Triple: [Alice campus, locatedInSettlement, Alice]
Generated description
Alice is a small town in the Eastern Cape province of South Africa, known for its university campus and historical significance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Alice
Target entity description: Alice is a small town in the Eastern Cape province of South Africa, known for its university campus and historical significance.
  • A. Alice chosen
    Alice is a small town in South Africa’s Eastern Cape province, known as an educational center and for its historical significance in the region.
  • B. Alice
    Alice is a feminine given name of Old French and Germanic origin, commonly used in English-speaking countries and popularized by literary works such as "Alice's Adventures in Wonderland."
  • C. Alice
    Alice is an American sitcom that aired from the mid-1970s to the mid-1980s, following a widowed waitress working at a roadside diner and the quirky people in her life.
  • D. Alice
    Alice is the superhuman protagonist of the Resident Evil film series, known for battling bioengineered monsters and the Umbrella Corporation in a post-apocalyptic world.
  • E. Alice
    Alice is a fictional character associated with mosquitoes, likely personifying or representing them in a narrative or creative context.
  • 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_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d731a5d5248190badfc5a8ab0215d6 completed April 9, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69de235fe7748190ba004f889da389ff completed April 14, 2026, 11:22 a.m.
NEDg Description generation batch_69de271ee56c81908d2f690f31c2d2db completed April 14, 2026, 11:38 a.m.
NED2 Entity disambiguation (via description) batch_69de2e05fdb08190b880f9158b14118b completed April 14, 2026, 12:07 p.m.
Created at: April 8, 2026, 9:16 p.m.