Triple
T17325999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cholpon-Ata petroglyphs |
E420688
|
entity |
| Predicate | culturalContext |
P36
|
FINISHED |
| Object | Saka |
E123639
|
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: Saka | Statement: [Cholpon-Ata petroglyphs, culturalContext, Saka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saka Context triple: [Cholpon-Ata petroglyphs, culturalContext, Saka]
-
A.
Saka
chosen
Saka is an ancient Eastern Iranian language once spoken by the Saka people in the Tarim Basin region of Central Asia.
-
B.
Sakaar
Sakaar is a chaotic, trash-covered planet ruled by the Grandmaster in the Marvel Cinematic Universe, known for its gladiatorial contests and bizarre cosmic detritus.
-
C.
Shuka
Shuka is a Japanese animation studio known for producing the later seasons and related works of the urban fantasy anime series Durarara!!.
-
D.
Sikinos
Sikinos is a small, tranquil Greek island in the Cyclades known for its traditional villages, rugged landscapes, and unspoiled, low-key tourism.
-
E.
Suo-Gân
Suo-Gân is a traditional Welsh lullaby known for its gentle melody and soothing, lyrical character.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439d24e548190a766dd246a4d63d4 |
completed | April 19, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c4c2dc08190b60982abc9ac7c9c |
completed | May 11, 2026, 7:59 a.m. |
Created at: April 10, 2026, 5:43 a.m.