Triple
T21428505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Thursday |
E528622
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Shahid Latief
Shahid Latief is an actor known for appearing in the Indian thriller film "A Thursday."
|
E1484140
|
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: Shahid Latief | Statement: [A Thursday, castMember, Shahid Latief]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shahid Latief Context triple: [A Thursday, castMember, Shahid Latief]
-
A.
Khalid Ashraf
Khalid Ashraf is a computer scientist and deep learning researcher known for co-designing the efficient convolutional neural network architecture SqueezeNet.
-
B.
Waheed Rahman
Waheed Rahman is a notable individual significant enough in his community or institution to have a hall named in his honor, reflecting his contributions or legacy.
-
C.
Khalil Mirza
Khalil Mirza was a historical figure of the Aq Qoyunlu dynasty, known primarily as a son of the Turkmen ruler Uzun Hasan.
-
D.
Arif Masood
Arif Masood is a Pakistani architect best known for designing the iconic Pakistan Monument in Islamabad.
-
E.
Shahid Amin
Shahid Amin is an Indian historian known for his influential contributions to the Subaltern Studies collective, particularly his work on peasant consciousness, memory, and the writing of history from below.
- 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: Shahid Latief Triple: [A Thursday, castMember, Shahid Latief]
Generated description
Shahid Latief is an actor known for appearing in the Indian thriller film "A Thursday."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shahid Latief Target entity description: Shahid Latief is an actor known for appearing in the Indian thriller film "A Thursday."
-
A.
Khalid Ashraf
Khalid Ashraf is a computer scientist and deep learning researcher known for co-designing the efficient convolutional neural network architecture SqueezeNet.
-
B.
Waheed Rahman
Waheed Rahman is a notable individual significant enough in his community or institution to have a hall named in his honor, reflecting his contributions or legacy.
-
C.
Khalil Mirza
Khalil Mirza was a historical figure of the Aq Qoyunlu dynasty, known primarily as a son of the Turkmen ruler Uzun Hasan.
-
D.
Arif Masood
Arif Masood is a Pakistani architect best known for designing the iconic Pakistan Monument in Islamabad.
-
E.
Shahid Amin
Shahid Amin is an Indian historian known for his influential contributions to the Subaltern Studies collective, particularly his work on peasant consciousness, memory, and the writing of history from below.
- 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b3e74bcc81909ad66e3c59152ffc |
completed | April 22, 2026, 11:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09c2aa56b081909ddfc07b7b5fd60e |
completed | May 17, 2026, 1:29 p.m. |
| NEDg | Description generation | batch_6a09c3a036408190a759223303268183 |
completed | May 17, 2026, 1:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09c49aa5b881908ac2e920684a9fa2 |
completed | May 17, 2026, 1:37 p.m. |
Created at: April 16, 2026, 5:49 p.m.