Triple
T18240801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Megrelia |
E436803
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Abasha |
—
|
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: Abasha | Statement: [Megrelia, hasCity, Abasha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abasha Context triple: [Megrelia, hasCity, Abasha]
-
A.
Abasha
chosen
Abasha is a small town in western Georgia’s Samegrelo region, known as a local administrative and cultural center.
-
B.
Abasa
Abasa is the 80th chapter of the Qur'an, known for its admonition regarding a moment when the Prophet Muhammad frowned at a blind man seeking guidance.
-
C.
Abunayyan
Abunayyan is a prominent Saudi family name associated with influential figures in business and public life in Saudi Arabia.
-
D.
Derabish
Derabish is a town and administrative block in the Kendrapara district of the Indian state of Odisha.
-
E.
Akhras
Akhras is a Syrian-origin family name best known for being the maiden surname of Asma al-Assad, the First Lady of Syria.
- 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.