Triple
T25275944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tunduma–Nakonde border |
E633695
|
entity |
| Predicate | hasBorderTownOnTanzanianSide |
P159091
|
FINISHED |
| Object | Tunduma |
—
|
NE NERFINISHED |
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: Tunduma | Statement: [Tunduma–Nakonde border, hasBorderTownOnTanzanianSide, Tunduma]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderTownOnTanzanianSide Context triple: [Tunduma–Nakonde border, hasBorderTownOnTanzanianSide, Tunduma]
-
A.
hasBorderTownOnMyanmarSide
Indicates that a town is located on the Myanmar side of a border shared with another country.
-
B.
regionWithinTanzania
Indicates that one region is geographically located within the national boundaries of Tanzania.
-
C.
borderDistanceToMalawi_km
Indicates the distance in kilometers from an entity’s border to the border of Malawi.
-
D.
borderTypeWithKenya
Indicates the type or nature of the border relationship that an entity shares with Kenya.
-
E.
hasBorderTownOnIndianSide
Indicates that a location has a corresponding town situated on the Indian side of an international border.
- F. None of above. chosen
Provenance (4 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_69e75a92f48881909974ff9c11150a2e |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49377411c8190b2188de444d76795 |
completed | May 1, 2026, 11:50 a.m. |
| PDg | Predicate description generation | batch_69f497b8abb88190bb672cf6907c4b8d |
completed | May 1, 2026, 12:08 p.m. |
Created at: April 21, 2026, 1:17 p.m.