Triple
T3250441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weiss |
E68163
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Brian Weiss
Brian Weiss is an American psychiatrist and author best known for popularizing past-life regression therapy through his bestselling books and public lectures.
|
E340904
|
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: Brian Weiss | Statement: [Weiss, hasNotableBearer, Brian Weiss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Weiss Context triple: [Weiss, hasNotableBearer, Brian Weiss]
-
A.
Steve Weissman
Steve Weissman is an American political activist and writer best known for his leadership role in the 1964 Berkeley Free Speech Movement.
-
B.
Dashiell Weinstein
Dashiell Weinstein is one of the children of disgraced film producer Harvey Weinstein.
-
C.
Chris Lebenzon
Chris Lebenzon is an American film editor known for his long-time collaborations with directors like Tim Burton and Tony Scott on major Hollywood films.
-
D.
Daniel Auster
Daniel Auster was a prominent Zionist politician and lawyer who served as mayor of Jerusalem during the British Mandate period.
-
E.
Marc Roskin
Marc Roskin is a television producer and director best known for his work on genre and adventure series such as "The Librarians."
- 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: Brian Weiss Triple: [Weiss, hasNotableBearer, Brian Weiss]
Generated description
Brian Weiss is an American psychiatrist and author best known for popularizing past-life regression therapy through his bestselling books and public lectures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brian Weiss Target entity description: Brian Weiss is an American psychiatrist and author best known for popularizing past-life regression therapy through his bestselling books and public lectures.
-
A.
Steve Weissman
Steve Weissman is an American political activist and writer best known for his leadership role in the 1964 Berkeley Free Speech Movement.
-
B.
Dashiell Weinstein
Dashiell Weinstein is one of the children of disgraced film producer Harvey Weinstein.
-
C.
Chris Lebenzon
Chris Lebenzon is an American film editor known for his long-time collaborations with directors like Tim Burton and Tony Scott on major Hollywood films.
-
D.
Daniel Auster
Daniel Auster was a prominent Zionist politician and lawyer who served as mayor of Jerusalem during the British Mandate period.
-
E.
Marc Roskin
Marc Roskin is a television producer and director best known for his work on genre and adventure series such as "The Librarians."
- 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf40f7908190a450c3136fccb020 |
completed | March 8, 2026, 5:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2776934108190ac405ba5ebd47084 |
completed | March 12, 2026, 8:20 a.m. |
| NEDg | Description generation | batch_69b27c2c16188190af03674ead3944de |
completed | March 12, 2026, 8:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b27ca63b1c8190ac6f67aef6d2c7e1 |
completed | March 12, 2026, 8:43 a.m. |
Created at: March 8, 2026, 3:09 p.m.