Triple
T3758478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tunis Governorate |
E82104
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
El Omrane
El Omrane is a district of Tunis, Tunisia, known as a largely residential urban area within the capital’s metropolitan region.
|
E385746
|
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: El Omrane | Statement: [Tunis Governorate, contains, El Omrane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: El Omrane Context triple: [Tunis Governorate, contains, El Omrane]
-
A.
El Tebbin
El Tebbin is an industrial district in southern Cairo, Egypt, known for its steel and heavy manufacturing facilities.
-
B.
Bir el Gubi
Bir el Gubi was a strategically important desert battlefield in Libya during World War II, known for significant clashes between British Commonwealth and Italian-German forces.
-
C.
Murzuq
Murzuq is an oasis town in southwestern Libya that historically served as an important Saharan trade and caravan center in the Fezzan region.
-
D.
Shuja
Shuja is a given name most notably associated with Shuja Shah Durrani, a 19th-century ruler of the Durrani Empire in Afghanistan.
-
E.
El Maasara
El Maasara is a district and suburban area in the southern part of Greater Cairo, Egypt, known for its residential neighborhoods and industrial zones.
- 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: El Omrane Triple: [Tunis Governorate, contains, El Omrane]
Generated description
El Omrane is a district of Tunis, Tunisia, known as a largely residential urban area within the capital’s metropolitan region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: El Omrane Target entity description: El Omrane is a district of Tunis, Tunisia, known as a largely residential urban area within the capital’s metropolitan region.
-
A.
El Tebbin
El Tebbin is an industrial district in southern Cairo, Egypt, known for its steel and heavy manufacturing facilities.
-
B.
Bir el Gubi
Bir el Gubi was a strategically important desert battlefield in Libya during World War II, known for significant clashes between British Commonwealth and Italian-German forces.
-
C.
Murzuq
Murzuq is an oasis town in southwestern Libya that historically served as an important Saharan trade and caravan center in the Fezzan region.
-
D.
Shuja
Shuja is a given name most notably associated with Shuja Shah Durrani, a 19th-century ruler of the Durrani Empire in Afghanistan.
-
E.
El Maasara
El Maasara is a district and suburban area in the southern part of Greater Cairo, Egypt, known for its residential neighborhoods and industrial zones.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbc20b20819095fedf803aadc53a |
completed | March 8, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e50f77fc8190b7774a7359118c9c |
completed | March 14, 2026, 4:33 a.m. |
| NEDg | Description generation | batch_69b4e5fe22f0819088effd8a0eae72e6 |
completed | March 14, 2026, 4:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4e671e02c819094cae2a3a2abb1b4 |
completed | March 14, 2026, 4:39 a.m. |
Created at: March 8, 2026, 3:35 p.m.