Triple
T15151217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanessa Hudgens |
E361945
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Hudgens
Hudgens is the surname of American actress and singer Vanessa Hudgens, best known for her breakout role in Disney's "High School Musical" franchise.
|
E1139888
|
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: Hudgens | Statement: [Vanessa Hudgens, familyName, Hudgens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hudgens Context triple: [Vanessa Hudgens, familyName, Hudgens]
-
A.
Hannen
Hannen is an English surname associated with several notable figures, including actors and judges, in British history.
-
B.
Hucknall
Hucknall is a market town in Nottinghamshire, England, historically known for its coal mining industry and as the burial place of the poet Lord Byron.
-
C.
Hoodi
Hoodi is a rapidly developing suburban neighborhood in eastern Bengaluru, India, known for its residential complexes, tech parks, and proximity to major IT hubs.
-
D.
Hutson
Hutson is a surname most notably associated with Don Hutson, a pioneering American football wide receiver regarded as one of the sport’s earliest stars.
-
E.
Hichens
Hichens is an English surname most notably associated with figures such as novelist Robert Hichens.
- 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: Hudgens Triple: [Vanessa Hudgens, familyName, Hudgens]
Generated description
Hudgens is the surname of American actress and singer Vanessa Hudgens, best known for her breakout role in Disney's "High School Musical" franchise.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hudgens Target entity description: Hudgens is the surname of American actress and singer Vanessa Hudgens, best known for her breakout role in Disney's "High School Musical" franchise.
-
A.
Hannen
Hannen is an English surname associated with several notable figures, including actors and judges, in British history.
-
B.
Hucknall
Hucknall is a market town in Nottinghamshire, England, historically known for its coal mining industry and as the burial place of the poet Lord Byron.
-
C.
Hoodi
Hoodi is a rapidly developing suburban neighborhood in eastern Bengaluru, India, known for its residential complexes, tech parks, and proximity to major IT hubs.
-
D.
Hutson
Hutson is a surname most notably associated with Don Hutson, a pioneering American football wide receiver regarded as one of the sport’s earliest stars.
-
E.
Hichens
Hichens is an English surname most notably associated with figures such as novelist Robert Hichens.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00609040081908c849475a2fa6443 |
completed | April 15, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febff44ef081908db5826c2626df06 |
completed | May 9, 2026, 5:02 a.m. |
| NEDg | Description generation | batch_69fec09c3bcc819098c8425e5606a6e6 |
completed | May 9, 2026, 5:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fec12b674c8190b2919144d5c1a489 |
completed | May 9, 2026, 5:07 a.m. |
Created at: April 10, 2026, 3:07 a.m.