Triple
T20502414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akram Khan |
E503337
|
entity |
| Predicate | choreographed |
P12047
|
FINISHED |
| Object | Xenos |
—
|
NE NERFINISHED |
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: Xenos | Statement: [Akram Khan, choreographed, Xenos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xenos Context triple: [Akram Khan, choreographed, Xenos]
-
A.
Xenos
chosen
Xenos is a contemporary dance-theatre production by acclaimed choreographer Akram Khan that explores themes of war, memory, and colonialism through the story of an Indian soldier in World War I.
-
B.
Xan
Xan is a short, informal diminutive of the given name Xander.
-
C.
Xilleon
Xilleon is a family of system-on-chip processors developed by ATI Technologies for use in digital television and set-top box applications.
-
D.
Xenith
Xenith is a sports equipment company best known for designing innovative, safety-focused football helmets and protective gear.
-
E.
Xeni
Xeni is an American journalist, blogger, and media personality best known as a co-editor of the influential tech and culture blog Boing Boing.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dc272a481909329ecd1560989ef |
completed | April 20, 2026, 9:42 p.m. |
Created at: April 16, 2026, 11:35 a.m.