Triple
T20258243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Josh Evans |
E498760
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Glam
Glam is a creative work associated with Josh Evans, likely a film or artistic project that showcases his style and thematic interests.
|
E1420854
|
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: Glam | Statement: [Josh Evans, notableWork, Glam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glam Context triple: [Josh Evans, notableWork, Glam]
-
A.
Glam
"Glam" is a track from Christina Aguilera's album *Bionic*, known for its fashion-themed lyrics and electro-pop production.
-
B.
GLAM
GLAM is the collective name for the University of Oxford’s network of gardens, libraries, and museums that steward and showcase its cultural and scientific collections.
-
C.
Glamorous
"Glamorous" is a 2007 hip hop and R&B song by American singer Fergie featuring Ludacris, known for its catchy chorus and themes of maintaining humility despite wealth and fame.
-
D.
Glamour
Glamour is a popular international women's magazine known for its coverage of fashion, beauty, lifestyle, and celebrity culture.
-
E.
Glitz
Glitz is a crime novel by Elmore Leonard that follows a tough Miami cop entangled with a vengeful ex-con and the seedy underworld of Atlantic City.
- 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: Glam Triple: [Josh Evans, notableWork, Glam]
Generated description
Glam is a creative work associated with Josh Evans, likely a film or artistic project that showcases his style and thematic interests.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Glam Target entity description: Glam is a creative work associated with Josh Evans, likely a film or artistic project that showcases his style and thematic interests.
-
A.
Glam
"Glam" is a track from Christina Aguilera's album *Bionic*, known for its fashion-themed lyrics and electro-pop production.
-
B.
GLAM
GLAM is the collective name for the University of Oxford’s network of gardens, libraries, and museums that steward and showcase its cultural and scientific collections.
-
C.
Glamorous
"Glamorous" is a 2007 hip hop and R&B song by American singer Fergie featuring Ludacris, known for its catchy chorus and themes of maintaining humility despite wealth and fame.
-
D.
Glamour
Glamour is a popular international women's magazine known for its coverage of fashion, beauty, lifestyle, and celebrity culture.
-
E.
Glitz
Glitz is a crime novel by Elmore Leonard that follows a tough Miami cop entangled with a vengeful ex-con and the seedy underworld of Atlantic City.
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674c7296c819092860942de8f28d5 |
completed | April 20, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08552c65488190922fc54374072e69 |
completed | May 16, 2026, 11:29 a.m. |
| NEDg | Description generation | batch_6a0855d7d87481908ff14d53a2ac94f7 |
completed | May 16, 2026, 11:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0856da3e748190866c328a6c61b3d8 |
completed | May 16, 2026, 11:36 a.m. |
Created at: April 11, 2026, 11:41 p.m.