Triple
T4810422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dodoma |
E107054
|
entity |
| Predicate | countryCapitalFunction |
P60266
|
FINISHED |
| Object | seat of the National Assembly of Tanzania |
—
|
LITERAL 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: seat of the National Assembly of Tanzania | Statement: [Dodoma, countryCapitalFunction, seat of the National Assembly of Tanzania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryCapitalFunction Context triple: [Dodoma, countryCapitalFunction, seat of the National Assembly of Tanzania]
-
A.
countryCapitalContext
Indicates that one entity serves as the capital city of the specified country in a given contextual or temporal setting.
-
B.
countryCapitalOf
Indicates that a country serves as the capital location for a specified political or geographic entity.
-
C.
regionCapital
Indicates that one entity is the capital city or administrative center of a specified region.
-
D.
hostsCapitalOf
Indicates that one location serves as the capital city of another administrative or political entity.
-
E.
cityAsCapitalOf
Indicates that a city serves as the official capital of a specified political or administrative entity.
- 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_69bd43f779448190b92885cb70abb6c2 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1c43a48190a65e56b1624a2339 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6ff731188190a9903602122d4ff9 |
completed | March 20, 2026, 4:04 p.m. |
Created at: March 20, 2026, 1:23 p.m.