Triple
T17154874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salmaniya campus |
E416318
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Salmaniya district
Salmaniya district is a neighborhood in Manama, Bahrain, known for hosting major institutions such as the Salmaniya Medical Complex and educational campuses.
|
E1252885
|
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: Salmaniya district | Statement: [Salmaniya campus, locatedIn, Salmaniya district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salmaniya district Context triple: [Salmaniya campus, locatedIn, Salmaniya district]
-
A.
Miyan Nasheen District
Miyan Nasheen District is an administrative district located in the northern part of Kandahar Province in southern Afghanistan.
-
B.
Sheema District
Sheema District is an administrative district in southwestern Uganda known for its predominantly rural communities and agricultural-based economy.
-
C.
Khadir District
Khadir District is an administrative district located within Daykundi Province in central Afghanistan.
-
D.
Gelan District
Gelan District is an administrative district in southeastern Afghanistan, located within Ghazni Province.
-
E.
Badr District
Badr District is an administrative district within Jordan’s capital region, forming part of the greater metropolitan area of Amman.
- 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: Salmaniya district Triple: [Salmaniya campus, locatedIn, Salmaniya district]
Generated description
Salmaniya district is a neighborhood in Manama, Bahrain, known for hosting major institutions such as the Salmaniya Medical Complex and educational campuses.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Salmaniya district Target entity description: Salmaniya district is a neighborhood in Manama, Bahrain, known for hosting major institutions such as the Salmaniya Medical Complex and educational campuses.
-
A.
Miyan Nasheen District
Miyan Nasheen District is an administrative district located in the northern part of Kandahar Province in southern Afghanistan.
-
B.
Sheema District
Sheema District is an administrative district in southwestern Uganda known for its predominantly rural communities and agricultural-based economy.
-
C.
Khadir District
Khadir District is an administrative district located within Daykundi Province in central Afghanistan.
-
D.
Gelan District
Gelan District is an administrative district in southeastern Afghanistan, located within Ghazni Province.
-
E.
Badr District
Badr District is an administrative district within Jordan’s capital region, forming part of the greater metropolitan area of Amman.
- 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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f40a6b7c8190838e588c4fd81d95 |
completed | April 18, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01415f3cd481908e96ca294cf3b247 |
completed | May 11, 2026, 2:39 a.m. |
| NEDg | Description generation | batch_6a01422c0f088190b162c7086bc93585 |
completed | May 11, 2026, 2:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0142f274ec819081eb15a3ea0e1b13 |
completed | May 11, 2026, 2:46 a.m. |
Created at: April 10, 2026, 5:37 a.m.