Triple
T18240800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Megrelia |
E436803
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Senaki |
—
|
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: Senaki | Statement: [Megrelia, hasCity, Senaki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Senaki Context triple: [Megrelia, hasCity, Senaki]
-
A.
Senaki
chosen
Senaki is a town in western Georgia that serves as an important local administrative and transportation center in the Samegrelo region.
-
B.
Sogakope
Sogakope is a town in southeastern Ghana known for its location along the lower Volta River and its role as a local commercial and transportation hub.
-
C.
Tsorona
Tsorona is a town in the Tigray region of northern Ethiopia, near the Eritrean border, known for being a strategic site in the Eritrean–Ethiopian conflicts.
-
D.
Nabaloi
Nabaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in the Benguet region of Luzon.
-
E.
Syeni
Syeni is a figure from Hindu mythology known primarily as one of the wives of the sage Kashyapa.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f7e287548190b666a990e5b168b0 |
completed | April 19, 2026, 3:42 p.m. |
Created at: April 10, 2026, 10:33 a.m.