Triple
T18710435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marjane Satrapi |
E457492
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Marjane
Marjane is a feminine given name most widely recognized through Iranian-French graphic novelist and filmmaker Marjane Satrapi.
|
E1338808
|
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: Marjane | Statement: [Marjane Satrapi, givenName, Marjane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marjane Context triple: [Marjane Satrapi, givenName, Marjane]
-
A.
Persepolis
Persepolis was the ceremonial heart of the ancient Achaemenid Persian Empire, renowned for its monumental palaces, grand staircases, and intricate reliefs.
-
B.
Persepolis
Persepolis is one of Iran’s most successful and popular football clubs, based in Tehran and renowned for its passionate fanbase and numerous domestic titles.
-
C.
Laleh
Laleh is an Iranian-Swedish singer-songwriter, producer, and former actress known for her eclectic pop music and introspective lyrics.
-
D.
Laila
Laila is a feminine given name used in various cultures, often associated with meanings like "night" or "dark beauty."
-
E.
Milena
Milena is the birth name of actress Mila Kunis, a Ukrainian-born American performer known for roles in "That '70s Show" and "Black Swan."
- 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: Marjane Triple: [Marjane Satrapi, givenName, Marjane]
Generated description
Marjane is a feminine given name most widely recognized through Iranian-French graphic novelist and filmmaker Marjane Satrapi.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marjane Target entity description: Marjane is a feminine given name most widely recognized through Iranian-French graphic novelist and filmmaker Marjane Satrapi.
-
A.
Persepolis
Persepolis was the ceremonial heart of the ancient Achaemenid Persian Empire, renowned for its monumental palaces, grand staircases, and intricate reliefs.
-
B.
Persepolis
Persepolis is one of Iran’s most successful and popular football clubs, based in Tehran and renowned for its passionate fanbase and numerous domestic titles.
-
C.
Laleh
Laleh is an Iranian-Swedish singer-songwriter, producer, and former actress known for her eclectic pop music and introspective lyrics.
-
D.
Laila
Laila is a feminine given name used in various cultures, often associated with meanings like "night" or "dark beauty."
-
E.
Milena
Milena is the birth name of actress Mila Kunis, a Ukrainian-born American performer known for roles in "That '70s Show" and "Black Swan."
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5671b34508190b6180f7d6ad50a58 |
completed | April 19, 2026, 11:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a052b3f247c8190922c4ce9f67301a0 |
completed | May 14, 2026, 1:54 a.m. |
| NEDg | Description generation | batch_6a052c6373088190a81e53963dac9c6f |
completed | May 14, 2026, 1:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a052d6f1f8081908810e99dff28b586 |
completed | May 14, 2026, 2:03 a.m. |
Created at: April 10, 2026, 11:50 a.m.