Triple
T5747598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kahn |
E126770
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Kahnn |
E126770
|
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: Kahnn | Statement: [Kahn, hasVariant, Kahnn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kahnn Context triple: [Kahn, hasVariant, Kahnn]
-
A.
Kaven
Kaven is one of the islands that make up Maloelap Atoll in the Marshall Islands, a Pacific island nation.
-
B.
Kahn
chosen
Kahn is a surname most famously associated with Louis Kahn, the influential 20th-century architect known for his monumental and timeless modernist buildings.
-
C.
Kashmore
Kashmore is a town in Pakistan’s Sindh province that serves as a regional hub near the Guddu Barrage on the Indus River.
-
D.
Kahle
Kahle is a surname most notably associated with Brewster Kahle, the American computer engineer and digital librarian who founded the Internet Archive.
-
E.
Kay Kavus
Kay Kavus is a legendary king of Iran in Ferdowsi’s epic Shahnameh, known for his hubris, ill-fated ambitions, and reliance on heroes like Rostam to rescue him from his own reckless schemes.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02885b0288190835809681a364b1f |
completed | March 22, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e30fe98819096ad6e09fbd463b5 |
completed | March 22, 2026, 11:41 p.m. |
Created at: March 22, 2026, 3:48 p.m.