Triple
T20148581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strange Clouds |
E491372
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object |
Lauriana Mae
Lauriana Mae is an American singer-songwriter known for her soulful, jazz- and R&B-influenced vocals and collaborations in contemporary pop and hip-hop music.
|
E1415111
|
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: Lauriana Mae | Statement: [Strange Clouds, featuresArtist, Lauriana Mae]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauriana Mae Context triple: [Strange Clouds, featuresArtist, Lauriana Mae]
-
A.
Lana
Lana is a river in Albania that flows through the capital city of Tirana before joining the Tirana River.
-
B.
Lana
Lana is a professional wrestler and television personality best known for her time in WWE, where she appeared prominently as a manager and in-ring performer.
-
C.
Lana
Lana is the seductive call girl who becomes the central love interest and catalyst for chaos in the 1983 film "Risky Business."
-
D.
Lana
Lana is the ISO 15924 four-letter code used to represent the Tai Tham script in international standards.
-
E.
Lana
Lana is the given name of actress Lana Condor, best known for starring in the "To All the Boys I've Loved Before" film series.
- 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: Lauriana Mae Triple: [Strange Clouds, featuresArtist, Lauriana Mae]
Generated description
Lauriana Mae is an American singer-songwriter known for her soulful, jazz- and R&B-influenced vocals and collaborations in contemporary pop and hip-hop music.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lauriana Mae Target entity description: Lauriana Mae is an American singer-songwriter known for her soulful, jazz- and R&B-influenced vocals and collaborations in contemporary pop and hip-hop music.
-
A.
Lana
Lana is the ISO 15924 four-letter code used to represent the Tai Tham script in international standards.
-
B.
Lana
Lana is a river in Albania that flows through the capital city of Tirana before joining the Tirana River.
-
C.
Lana
Lana is a professional wrestler and television personality best known for her time in WWE, where she appeared prominently as a manager and in-ring performer.
-
D.
Lana
Lana is the seductive call girl who becomes the central love interest and catalyst for chaos in the 1983 film "Risky Business."
-
E.
Lana
Lana is a cheerful, blue-haired sorceress and original playable character introduced in the game Hyrule Warriors.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667a0075c8190a5c4de53a0caa7f6 |
completed | April 20, 2026, 5:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08346f7b708190b006704558b25a67 |
completed | May 16, 2026, 9:10 a.m. |
| NEDg | Description generation | batch_6a08357acba08190be9fcedf1ea0f19d |
completed | May 16, 2026, 9:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0836a5cfdc81908806d83acd257acd |
completed | May 16, 2026, 9:19 a.m. |
Created at: April 11, 2026, 11:33 p.m.