Triple
T9122964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mini |
E218900
|
entity |
| Predicate | hasFriend |
P8712
|
FINISHED |
| Object |
Rahmat
Rahmat is an individual known primarily as a friend of Mini.
|
E218899
|
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: Rahmat | Statement: [Mini, hasFriend, Rahmat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rahmat Context triple: [Mini, hasFriend, Rahmat]
-
A.
Rahmat
Rahmat is the central character of Rabindranath Tagore’s short story "Kabuliwala," an Afghan fruit seller in Kolkata whose poignant bond with a young girl highlights themes of love, separation, and humanity.
-
B.
Ar-Rahim
Ar-Rahim is one of the 99 Names of Allah in Islam, signifying God as the Especially Merciful whose compassion is continuously bestowed upon His creation.
-
C.
Rabbani
Rabbani is a surname most prominently associated with Burhanuddin Rabbani, a key Afghan political and religious leader who served as President of Afghanistan during the 1990s.
-
D.
Surallah
Surallah is a landlocked agricultural municipality in the province of South Cotabato in the Philippines, known for its rice and corn production and its role as a commercial hub in the Allah Valley.
-
E.
Habib
Habib is a masculine given name of Arabic origin commonly used in North Africa and the Middle East.
- 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: Rahmat Triple: [Mini, hasFriend, Rahmat]
Generated description
Rahmat is an individual known primarily as a friend of Mini.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rahmat Target entity description: Rahmat is an individual known primarily as a friend of Mini.
-
A.
Rahmat
chosen
Rahmat is the central character of Rabindranath Tagore’s short story "Kabuliwala," an Afghan fruit seller in Kolkata whose poignant bond with a young girl highlights themes of love, separation, and humanity.
-
B.
Ar-Rahim
Ar-Rahim is one of the 99 Names of Allah in Islam, signifying God as the Especially Merciful whose compassion is continuously bestowed upon His creation.
-
C.
Rabbani
Rabbani is a surname most prominently associated with Burhanuddin Rabbani, a key Afghan political and religious leader who served as President of Afghanistan during the 1990s.
-
D.
Surallah
Surallah is a landlocked agricultural municipality in the province of South Cotabato in the Philippines, known for its rice and corn production and its role as a commercial hub in the Allah Valley.
-
E.
Habib
Habib is a masculine given name of Arabic origin commonly used in North Africa and the Middle East.
- F. None of above.
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_69ca83dddd548190983b96c664f7f367 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8b5fa188190be6465e74cf26915 |
completed | April 1, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0308ff628819083f02bf71eb40c5b |
completed | April 3, 2026, 9:26 p.m. |
| NEDg | Description generation | batch_69d0318ef52c8190bfa0bef6a8d41daa |
completed | April 3, 2026, 9:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d03571c4648190bd546152c61c55a5 |
completed | April 3, 2026, 9:47 p.m. |
Created at: March 30, 2026, 7:17 p.m.