Triple
T15492434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauritz Stiller |
E378726
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object |
Moshe Stiller
Moshe Stiller, better known as Mauritz Stiller, was a pioneering Swedish film director of the silent era who helped launch Greta Garbo’s career.
|
E1161236
|
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: Moshe Stiller | Statement: [Mauritz Stiller, birthName, Moshe Stiller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moshe Stiller Context triple: [Mauritz Stiller, birthName, Moshe Stiller]
-
A.
Moshe Diamant
Moshe Diamant is a film producer known for his work on action and science fiction movies, including the 1994 time-travel film "Timecop."
-
B.
Yehuda Efroni
Yehuda Efroni was an Israeli actor known for his work in film, television, and theater.
-
C.
Joseph Markovitch
Joseph Markovitch was the father of French photographer and painter Dora Maar, a key figure in the Surrealist movement and companion of Pablo Picasso.
-
D.
Eran Riklis
Eran Riklis is an Israeli film director known for socially and politically themed dramas such as "The Syrian Bride" and "Lemon Tree."
-
E.
Michael Sela
Michael Sela was an Israeli immunologist renowned for his pioneering work on synthetic antigens and for helping develop the multiple sclerosis drug Copaxone.
- 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: Moshe Stiller Triple: [Mauritz Stiller, birthName, Moshe Stiller]
Generated description
Moshe Stiller, better known as Mauritz Stiller, was a pioneering Swedish film director of the silent era who helped launch Greta Garbo’s career.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Moshe Stiller Target entity description: Moshe Stiller, better known as Mauritz Stiller, was a pioneering Swedish film director of the silent era who helped launch Greta Garbo’s career.
-
A.
Moshe Diamant
Moshe Diamant is a film producer known for his work on action and science fiction movies, including the 1994 time-travel film "Timecop."
-
B.
Yehuda Efroni
Yehuda Efroni was an Israeli actor known for his work in film, television, and theater.
-
C.
Joseph Markovitch
Joseph Markovitch was the father of French photographer and painter Dora Maar, a key figure in the Surrealist movement and companion of Pablo Picasso.
-
D.
Eran Riklis
Eran Riklis is an Israeli film director known for socially and politically themed dramas such as "The Syrian Bride" and "Lemon Tree."
-
E.
Michael Sela
Michael Sela was an Israeli immunologist renowned for his pioneering work on synthetic antigens and for helping develop the multiple sclerosis drug Copaxone.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fad723481908d2aa33e8f065f2f |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3660fc6c81908caf1729260a8338 |
completed | May 9, 2026, 1:28 p.m. |
| NEDg | Description generation | batch_69ff373558c88190983792d12956886e |
completed | May 9, 2026, 1:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff37c1b1e081909662b37eb5a2da1a |
completed | May 9, 2026, 1:33 p.m. |
Created at: April 10, 2026, 3:49 a.m.