Triple
T8622081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GEL |
E204189
|
entity |
| Predicate | hasSubunit |
P747
|
FINISHED |
| Object | tetri |
E112393
|
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: tetri | Statement: [GEL, hasSubunit, tetri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: tetri Context triple: [GEL, hasSubunit, tetri]
-
A.
tetri
chosen
The tetri is the fractional monetary unit of Georgia, used as a subdivision of the Georgian lari.
-
B.
tet
tet is the ISO 639-1 language code for Tetum, an Austronesian language spoken primarily in East Timor.
-
C.
Tetritsqaro
Tetritsqaro is a town in southeastern Georgia that serves as a local administrative and transportation center within the Kvemo Kartli region.
-
D.
Tentyris
Tentyris is the ancient Greek name for the Egyptian city of Dendera, renowned for its well-preserved temple complex dedicated primarily to the goddess Hathor.
-
E.
Tetro
Tetro is a 2009 drama film directed by Francis Ford Coppola, in which Maribel Verdú plays a key supporting role in a story about fractured family relationships and artistic rivalry in Buenos Aires.
- 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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4717f0e88190aaf0fd45bf726941 |
completed | March 31, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebbdd6aac819091f6dd12815c3d94 |
completed | April 2, 2026, 6:56 p.m. |
Created at: March 30, 2026, 6:26 p.m.