Triple
T9550760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte |
E230414
|
entity |
| Predicate | hasShortForm |
P43
|
FINISHED |
| Object |
Lotte
Lotte is a common diminutive form of the given name Charlotte, used in several European languages.
|
E805400
|
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: Lotte | Statement: [Charlotte, hasShortForm, Lotte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lotte Context triple: [Charlotte, hasShortForm, Lotte]
-
A.
Lotte Group
Lotte Group is a major South Korean-Japanese multinational conglomerate with diverse businesses spanning food, retail, tourism, chemicals, and entertainment.
-
B.
Hansol
Hansol is a locality in Ahmedabad, India, situated near Sardar Vallabhbhai Patel International Airport and known primarily as a residential and commercial area serving airport-related activities.
-
C.
Shinsegae Group
Shinsegae Group is a major South Korean retail conglomerate best known for its department stores, supermarkets, and diverse consumer-focused businesses.
-
D.
Lotte Orions
Lotte Orions was a Japanese professional baseball team in Nippon Professional Baseball, known as a predecessor to the Chiba Lotte Marines.
-
E.
Sojin
Sojin is a given name, often used in East Asian cultures, that can refer to various individuals in entertainment, arts, and other fields.
- 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: Lotte Triple: [Charlotte, hasShortForm, Lotte]
Generated description
Lotte is a common diminutive form of the given name Charlotte, used in several European languages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lotte Target entity description: Lotte is a common diminutive form of the given name Charlotte, used in several European languages.
-
A.
Lotte Group
Lotte Group is a major South Korean-Japanese multinational conglomerate with diverse businesses spanning food, retail, tourism, chemicals, and entertainment.
-
B.
Hansol
Hansol is a locality in Ahmedabad, India, situated near Sardar Vallabhbhai Patel International Airport and known primarily as a residential and commercial area serving airport-related activities.
-
C.
Shinsegae Group
Shinsegae Group is a major South Korean retail conglomerate best known for its department stores, supermarkets, and diverse consumer-focused businesses.
-
D.
Lotte Orions
Lotte Orions was a Japanese professional baseball team in Nippon Professional Baseball, known as a predecessor to the Chiba Lotte Marines.
-
E.
Sojin
Sojin is a given name, often used in East Asian cultures, that can refer to various individuals in entertainment, arts, and other fields.
- 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_69ca847d3be8819099c9dad2a7e786f1 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd991df7308190a56d95f195627513 |
completed | April 1, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14c85b9208190acf98fa985b0f01f |
completed | April 4, 2026, 5:38 p.m. |
| NEDg | Description generation | batch_69d14d0c39c88190a705470104dc7b80 |
completed | April 4, 2026, 5:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d14d79065081908a4e619c71e0d359 |
completed | April 4, 2026, 5:42 p.m. |
Created at: March 30, 2026, 8:02 p.m.