Triple
T6965159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In the Fade |
E161469
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Samia Chancrin
Samia Chancrin is an actress known for her role in the German crime thriller film "In the Fade."
|
E631648
|
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: Samia Chancrin | Statement: [In the Fade, castMember, Samia Chancrin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samia Chancrin Context triple: [In the Fade, castMember, Samia Chancrin]
-
A.
Naïma Kefi
Naïma Kefi is a Tunisian public figure best known as the wife of former Tunisian president Zine El Abidine Ben Ali.
-
B.
Wassila Ben Ammar
Wassila Ben Ammar was a prominent Tunisian political figure and the influential second wife of President Habib Bourguiba.
-
C.
Lina Ben Mhenni
Lina Ben Mhenni was a Tunisian blogger, activist, and outspoken critic of censorship whose online reporting became a prominent voice of the Arab Spring.
-
D.
Chadlia Saïda Farhat
Chadlia Saïda Farhat was the First Lady of Tunisia during the presidency of her husband, Beji Caid Essebsi.
-
E.
Fatima-Zohra Imalayen
Fatima-Zohra Imalayen, better known by her pen name Assia Djebar, was a prominent Algerian novelist, filmmaker, and academic whose work powerfully explored themes of colonialism, gender, and identity in the Maghreb.
- 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: Samia Chancrin Triple: [In the Fade, castMember, Samia Chancrin]
Generated description
Samia Chancrin is an actress known for her role in the German crime thriller film "In the Fade."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Samia Chancrin Target entity description: Samia Chancrin is an actress known for her role in the German crime thriller film "In the Fade."
-
A.
Naïma Kefi
Naïma Kefi is a Tunisian public figure best known as the wife of former Tunisian president Zine El Abidine Ben Ali.
-
B.
Wassila Ben Ammar
Wassila Ben Ammar was a prominent Tunisian political figure and the influential second wife of President Habib Bourguiba.
-
C.
Lina Ben Mhenni
Lina Ben Mhenni was a Tunisian blogger, activist, and outspoken critic of censorship whose online reporting became a prominent voice of the Arab Spring.
-
D.
Chadlia Saïda Farhat
Chadlia Saïda Farhat was the First Lady of Tunisia during the presidency of her husband, Beji Caid Essebsi.
-
E.
Fatima-Zohra Imalayen
Fatima-Zohra Imalayen, better known by her pen name Assia Djebar, was a prominent Algerian novelist, filmmaker, and academic whose work powerfully explored themes of colonialism, gender, and identity in the Maghreb.
- 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db1049e0819097099a0e9d15f787 |
completed | March 27, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c758a57b8481908cef7de9b3abf7a3 |
completed | March 28, 2026, 4:27 a.m. |
| NEDg | Description generation | batch_69c75afc74a88190b87284b9a07e8abb |
completed | March 28, 2026, 4:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c75ba456ec81908bd3ab9ade1954d4 |
completed | March 28, 2026, 4:40 a.m. |
Created at: March 27, 2026, 2:30 p.m.