Triple
T8712227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aliens |
E206803
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Jenette Goldstein
Jenette Goldstein is an American actress best known for her tough, memorable supporting roles in science fiction and action films of the 1980s and 1990s.
|
E788441
|
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: Jenette Goldstein | Statement: [Aliens, stars, Jenette Goldstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jenette Goldstein Context triple: [Aliens, stars, Jenette Goldstein]
-
A.
Linda Goldstein
Linda Goldstein is a music producer known for her work on projects such as the album "Simple Pleasures."
-
B.
Ilene Rosenzweig
Ilene Rosenzweig is a writer and editor best known for co-authoring lifestyle and design books with fashion designer Cynthia Rowley.
-
C.
Jan Goldstein
Jan Goldstein is an American novelist and inspirational speaker known for uplifting, emotionally driven fiction and motivational works.
-
D.
Suzanne Goldberg
Suzanne Goldberg is known as the wife of prominent 1960s Free Speech Movement leader Mario Savio.
-
E.
Suzanne Goldberg
Suzanne Goldberg is a prominent civil rights lawyer and legal scholar known for her work on free speech and equality issues in the United States.
- 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: Jenette Goldstein Triple: [Aliens, stars, Jenette Goldstein]
Generated description
Jenette Goldstein is an American actress best known for her tough, memorable supporting roles in science fiction and action films of the 1980s and 1990s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jenette Goldstein Target entity description: Jenette Goldstein is an American actress best known for her tough, memorable supporting roles in science fiction and action films of the 1980s and 1990s.
-
A.
Linda Goldstein
Linda Goldstein is a music producer known for her work on projects such as the album "Simple Pleasures."
-
B.
Ilene Rosenzweig
Ilene Rosenzweig is a writer and editor best known for co-authoring lifestyle and design books with fashion designer Cynthia Rowley.
-
C.
Jan Goldstein
Jan Goldstein is an American novelist and inspirational speaker known for uplifting, emotionally driven fiction and motivational works.
-
D.
Suzanne Goldberg
Suzanne Goldberg is known as the wife of prominent 1960s Free Speech Movement leader Mario Savio.
-
E.
Suzanne Goldberg
Suzanne Goldberg is a prominent civil rights lawyer and legal scholar known for her work on free speech and equality issues in the United States.
- 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5c32aebc8190ba19299ce9a18efd |
completed | March 31, 2026, 11:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d09b22da4c81909aacc9c4a6af379c |
completed | April 4, 2026, 5:01 a.m. |
| NEDg | Description generation | batch_69d09ca202f88190b21b89e61b1596ff |
completed | April 4, 2026, 5:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d09d914d688190af609c4485c746cc |
completed | April 4, 2026, 5:11 a.m. |
Created at: March 30, 2026, 6:35 p.m.