Triple
T7131606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mande |
E166201
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object | Tura |
E212962
|
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: Tura | Statement: [Mande, hasLanguage, Tura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tura Context triple: [Mande, hasLanguage, Tura]
-
A.
Tura
chosen
Tura is a prominent town in the Indian state of Meghalaya, serving as a major administrative, cultural, and economic center in the Garo Hills region.
-
B.
Tura
Tura is a district in southern Cairo, Egypt, historically known for its limestone quarries used in ancient Egyptian monuments.
-
C.
Turi
Turi is a small town and comune in the Apulia region of southern Italy, known for its agricultural production—especially cherries—and its historic architecture.
-
D.
Tarusa
Tarusa is a small historic town in western Russia known for its scenic location on the Oka River and its associations with Russian artists and writers.
-
E.
Tain
Tain is a historic town in the Highlands of Scotland, known as one of the country’s oldest royal burghs and a regional administrative and judicial center.
- 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_69c68884a9388190af42f90d1c1a7151 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e66f15b88190bc1fb0f0a8af16a6 |
completed | March 27, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a33eea0481909f87e0813bc35b52 |
completed | March 28, 2026, 9:45 a.m. |
Created at: March 27, 2026, 2:44 p.m.