Triple
T2252387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lakhdar Brahimi |
E49645
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Lakhdar
Lakhdar is an Arabic masculine given name most notably borne by Algerian diplomat Lakhdar Brahimi.
|
E247116
|
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: Lakhdar | Statement: [Lakhdar Brahimi, givenName, Lakhdar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lakhdar Context triple: [Lakhdar Brahimi, givenName, Lakhdar]
-
A.
Sahnun
Sahnun was a prominent 9th-century Islamic jurist from North Africa whose compilation of legal opinions, the Mudawwana, became a foundational text of the Maliki school of Sunni jurisprudence.
-
B.
Belhamed
Belhamed is a locality in Libya that was the site of significant fighting during World War II’s North African campaign.
-
C.
Butrus
Butrus is an alternative transliteration of the Arabic given name "Boutros," itself derived from "Peter."
-
D.
Mohandessin
Mohandessin is a prominent, upscale district in Giza, Egypt, known for its residential neighborhoods, commercial avenues, and vibrant urban life.
-
E.
Al-Lakhmi
Al-Lakhmi was a prominent medieval Maliki jurist and legal scholar whose opinions significantly shaped the development of Maliki jurisprudence.
- 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: Lakhdar Triple: [Lakhdar Brahimi, givenName, Lakhdar]
Generated description
Lakhdar is an Arabic masculine given name most notably borne by Algerian diplomat Lakhdar Brahimi.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lakhdar Target entity description: Lakhdar is an Arabic masculine given name most notably borne by Algerian diplomat Lakhdar Brahimi.
-
A.
Sahnun
Sahnun was a prominent 9th-century Islamic jurist from North Africa whose compilation of legal opinions, the Mudawwana, became a foundational text of the Maliki school of Sunni jurisprudence.
-
B.
Belhamed
Belhamed is a locality in Libya that was the site of significant fighting during World War II’s North African campaign.
-
C.
Butrus
Butrus is an alternative transliteration of the Arabic given name "Boutros," itself derived from "Peter."
-
D.
Mohandessin
Mohandessin is a prominent, upscale district in Giza, Egypt, known for its residential neighborhoods, commercial avenues, and vibrant urban life.
-
E.
Al-Lakhmi
Al-Lakhmi was a prominent medieval Maliki jurist and legal scholar whose opinions significantly shaped the development of Maliki jurisprudence.
- 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_69a88aaa9250819095e127d0d77e8a32 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc11eb2708190bc5a3d152a3bb133 |
completed | March 7, 2026, 6:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6b1dd6fc8190bd762fb3a17258b0 |
completed | March 9, 2026, 6:39 a.m. |
| NEDg | Description generation | batch_69ae6bbdef14819084b96389435ca080 |
completed | March 9, 2026, 6:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae6c2cfac48190b0425088e79cd122 |
completed | March 9, 2026, 6:43 a.m. |
Created at: March 4, 2026, 7:47 p.m.