Triple
T14739477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kadeem Hardison |
E346303
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | K.C. Undercover |
E343255
|
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: K.C. Undercover | Statement: [Kadeem Hardison, notableWork, K.C. Undercover]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: K.C. Undercover Context triple: [Kadeem Hardison, notableWork, K.C. Undercover]
-
A.
K.C. Undercover
chosen
K.C. Undercover is a Disney Channel action-comedy television series starring Zendaya as a high school student who secretly works as a teenage spy.
-
B.
The Kenny
The Kenny is the affectionate nickname for Kenilworth Road, the historic home stadium of Luton Town Football Club in England.
-
C.
Undercovers
Undercovers is an American action-spy television series created by J.J. Abrams that follows a married couple who are reactivated as CIA agents.
-
D.
Undercover
Undercover is a book by former CIA officer and Watergate conspirator E. Howard Hunt, detailing his experiences in espionage and covert operations.
-
E.
Undercover
Undercover is a British television drama series that follows a lawyer uncovering shocking secrets about her husband and the justice system.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7345680819093e901233a064e48 |
completed | April 14, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb91fdf88190bdcc9a93289f6b7f |
completed | May 8, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:29 a.m.