Triple
T3633366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Kite Runner (film) |
E77009
|
entity |
| Predicate | originalLanguage |
P15
|
FINISHED |
| Object | Dari |
E109613
|
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: Dari | Statement: [The Kite Runner (film), originalLanguage, Dari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dari Context triple: [The Kite Runner (film), originalLanguage, Dari]
-
A.
Dari
chosen
Dari is a variety of the Persian language primarily spoken in Afghanistan and used in media, education, and government there.
-
B.
Dijlah
Dijlah is the Arabic name for the Tigris River, one of the major rivers of Western Asia flowing through Turkey, Syria, and Iraq.
-
C.
Bani
Bani was a daughter of the prominent Indian freedom fighter and lawyer Chittaranjan (C. R.) Das.
-
D.
Barshaini
Barshaini is a small Himalayan village in Himachal Pradesh, India, that serves as a popular base and trailhead for treks into the Parvati Valley and surrounding high-altitude landscapes.
-
E.
Dara
Dara is a given name most prominently associated with Dara Khosrowshahi, the Iranian-American businessman and CEO of Uber.
- 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_69ad85dd0be48190b738990cb20c4731 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc30457608190840fb5b33f9965c4 |
completed | March 8, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44f1af1c48190a72effe80959bfb3 |
completed | March 13, 2026, 5:53 p.m. |
Created at: March 8, 2026, 3:23 p.m.