Triple
T12684590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mardan District |
E303034
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Charsadda District |
E277515
|
NE FINISHED |
How this triple was built (2 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: Charsadda District | Statement: [Mardan District, borderedBy, Charsadda District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charsadda District Context triple: [Mardan District, borderedBy, Charsadda District]
-
A.
Charsadda District
chosen
Charsadda District is an administrative district in Pakistan’s Khyber Pakhtunkhwa province, known for its rich historical heritage and agricultural economy.
-
B.
Baabda District
Baabda District is an administrative district in the Mount Lebanon Governorate of Lebanon that includes key suburbs of Beirut and has historically been a significant political and military area.
-
C.
Gelan District
Gelan District is an administrative district in southeastern Afghanistan, located within Ghazni Province.
-
D.
Salhiya district
Salhiya district is a central neighborhood in Kuwait City known for its commercial complexes, offices, and residential areas.
-
E.
Khadir District
Khadir District is an administrative district located within Daykundi Province in central Afghanistan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961d7cd4c81909521839ef5859799 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af47b3d48190923e731c3733428a |
completed | May 3, 2026, 2:13 a.m. |
Created at: April 9, 2026, 5:21 p.m.