Triple
T14655735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julieta |
E344101
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Mariam Bachir
Mariam Bachir is a Spanish actress best known for her role in Pedro Almodóvar’s film "Julieta."
|
E1112936
|
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: Mariam Bachir | Statement: [Julieta, castMember, Mariam Bachir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mariam Bachir Context triple: [Julieta, castMember, Mariam Bachir]
-
A.
Fayza Lamari
Fayza Lamari is a former French handball player and the mother and influential advisor of football star Kylian Mbappé.
-
B.
Hadya Sher Ali
Hadya Sher Ali is a Pakistani woman known primarily for her brief marriage to British-Pakistani heart surgeon Hasnat Khan.
-
C.
Sajida Talfah
Sajida Talfah was the first wife and cousin of former Iraqi president Saddam Hussein and the mother of several of his children.
-
D.
Hanan al-Shaykh
Hanan al-Shaykh is a prominent Lebanese novelist and short story writer known for her bold explorations of gender, sexuality, and social norms in contemporary Arabic literature.
-
E.
Amina Hussein
Amina Hussein is the socially awkward, microbiology PhD student and lead guitarist whose journey of self-discovery anchors the British comedy series "We Are Lady Parts."
- 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: Mariam Bachir Triple: [Julieta, castMember, Mariam Bachir]
Generated description
Mariam Bachir is a Spanish actress best known for her role in Pedro Almodóvar’s film "Julieta."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mariam Bachir Target entity description: Mariam Bachir is a Spanish actress best known for her role in Pedro Almodóvar’s film "Julieta."
-
A.
Fayza Lamari
Fayza Lamari is a former French handball player and the mother and influential advisor of football star Kylian Mbappé.
-
B.
Hadya Sher Ali
Hadya Sher Ali is a Pakistani woman known primarily for her brief marriage to British-Pakistani heart surgeon Hasnat Khan.
-
C.
Sajida Talfah
Sajida Talfah was the first wife and cousin of former Iraqi president Saddam Hussein and the mother of several of his children.
-
D.
Hanan al-Shaykh
Hanan al-Shaykh is a prominent Lebanese novelist and short story writer known for her bold explorations of gender, sexuality, and social norms in contemporary Arabic literature.
-
E.
Amina Hussein
Amina Hussein is the socially awkward, microbiology PhD student and lead guitarist whose journey of self-discovery anchors the British comedy series "We Are Lady Parts."
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb51a562c819098971447db4b29f7 |
completed | April 14, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5de0b98819094c32765e4cb3f9c |
completed | May 8, 2026, 12:23 p.m. |
| NEDg | Description generation | batch_69fddd8d7da481909d38d9390770939c |
completed | May 8, 2026, 12:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdde23da708190b7eabeed6a9cb169 |
completed | May 8, 2026, 12:59 p.m. |
Created at: April 10, 2026, 1:27 a.m.