Triple
T2168296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marguerite Matisse |
E46961
|
entity |
| Predicate | depictedIn |
P626
|
FINISHED |
| Object |
Marguerite in a Straw Hat
Marguerite in a Straw Hat is a portrait painting by Henri Matisse depicting his daughter Marguerite wearing a straw hat.
|
E239734
|
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: Marguerite in a Straw Hat | Statement: [Marguerite Matisse, depictedIn, Marguerite in a Straw Hat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marguerite in a Straw Hat Context triple: [Marguerite Matisse, depictedIn, Marguerite in a Straw Hat]
-
A.
Mariquita
Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
-
B.
Michiko
Michiko is the former Empress of Japan and the wife of Emperor Emeritus Akihito, known for being the first commoner to marry into the Japanese imperial family.
-
C.
Totsuko
Totsuko is the former abbreviated name of Tokyo Tsushin Kogyo, the Japanese company that later became Sony.
-
D.
Haruko
Haruko, better known as Empress Shōken, was the consort of Emperor Meiji and a prominent Japanese empress noted for her support of modernization and social welfare.
-
E.
Hana
Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
- 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: Marguerite in a Straw Hat Triple: [Marguerite Matisse, depictedIn, Marguerite in a Straw Hat]
Generated description
Marguerite in a Straw Hat is a portrait painting by Henri Matisse depicting his daughter Marguerite wearing a straw hat.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marguerite in a Straw Hat Target entity description: Marguerite in a Straw Hat is a portrait painting by Henri Matisse depicting his daughter Marguerite wearing a straw hat.
-
A.
Mariquita
Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
-
B.
Michiko
Michiko is the former Empress of Japan and the wife of Emperor Emeritus Akihito, known for being the first commoner to marry into the Japanese imperial family.
-
C.
Totsuko
Totsuko is the former abbreviated name of Tokyo Tsushin Kogyo, the Japanese company that later became Sony.
-
D.
Haruko
Haruko, better known as Empress Shōken, was the consort of Emperor Meiji and a prominent Japanese empress noted for her support of modernization and social welfare.
-
E.
Hana
Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
- 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_69a88a184cbc8190877791f6552c2484 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbeadaed481908d6afa942d7155b8 |
completed | March 7, 2026, 5:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58f26334819095202544d37e6850 |
completed | March 9, 2026, 5:21 a.m. |
| NEDg | Description generation | batch_69ae5a2055488190855ac173d1e3ad11 |
completed | March 9, 2026, 5:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5a810b588190a1bb538be46b2010 |
completed | March 9, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:45 p.m.