Triple
T69805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Arden |
E1396
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Florence
Florence is the birth name of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics brand.
|
E19052
|
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: Florence | Statement: [Elizabeth Arden, givenName, Florence]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Florence Context triple: [Elizabeth Arden, givenName, Florence]
-
A.
Naples
Naples is a historic coastal city in southern Italy renowned for its rich cultural heritage, vibrant street life, and as the birthplace of pizza.
-
B.
Venice
Venice is a vibrant beachfront neighborhood on Los Angeles’s Westside known for its bohemian spirit, canals, boardwalk, and skate and surf culture.
-
C.
Milan
Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
-
D.
Turin
Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and economic hub.
-
E.
Rome
Rome is the historic capital of Italy and a major cultural and religious center of the world, renowned for its ancient Roman heritage, art, and architecture.
- 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: Florence Triple: [Elizabeth Arden, givenName, Florence]
Generated description
Florence is the birth name of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics brand.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Florence Target entity description: Florence is the birth name of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics brand.
-
A.
Naples
Naples is a historic coastal city in southern Italy renowned for its rich cultural heritage, vibrant street life, and as the birthplace of pizza.
-
B.
Venice
Venice is a vibrant beachfront neighborhood on Los Angeles’s Westside known for its bohemian spirit, canals, boardwalk, and skate and surf culture.
-
C.
Milan
Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
-
D.
Turin
Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and economic hub.
-
E.
Rome
Rome is the historic capital of Italy and a major cultural and religious center of the world, renowned for its ancient Roman heritage, art, and architecture.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f045d38819088f5f71e39fa1ee7 |
completed | Feb. 28, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2ce338f708190b9e5eba745d45ca6 |
completed | Feb. 28, 2026, 11:14 a.m. |
| NEDg | Description generation | batch_69a2cec41ab481908ec4886497212276 |
completed | Feb. 28, 2026, 11:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2cf3e80d08190aefb2651ee66b387 |
completed | Feb. 28, 2026, 11:19 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.