Triple
T8550880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vikram |
E202439
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Kasi |
E613283
|
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: Kasi | Statement: [Vikram, notableWork, Kasi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kasi Context triple: [Vikram, notableWork, Kasi]
-
A.
Kasi
chosen
Kasi is the first name of Kasi Lemmons, an American film director, actress, and screenwriter known for works like "Eve's Bayou" and "Harriet."
-
B.
Kas
Kas is the historical name of Shahrisabz, an ancient city in southern Uzbekistan renowned as the birthplace of Timur (Tamerlane) and for its significant Timurid-era architectural monuments.
-
C.
Kais
Kais is the given name of Kais Saied, the Tunisian politician and president known for his anti-corruption stance and consolidation of executive power.
-
D.
Kai
Kai is a masculine given name used in various cultures, often associated with meanings such as "sea," "forgiveness," or "victory" depending on its linguistic origin.
-
E.
Kai
Kai is the fictional half-Japanese, half-English outcast and skilled warrior portrayed by Keanu Reeves in the fantasy samurai film "47 Ronin."
- 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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe75589d8819096177ddbd3dafcb6 |
completed | March 31, 2026, 3:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6dc7f6fc8190addd5d2bbe1f4408 |
completed | April 2, 2026, 1:23 p.m. |
Created at: March 30, 2026, 6:19 p.m.