Triple
T9579600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | For the Cool in You |
E231134
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Kayo |
E579108
|
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: Kayo | Statement: [For the Cool in You, producer, Kayo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kayo Context triple: [For the Cool in You, producer, Kayo]
-
A.
Kayo
chosen
Kayo is a contributor to the Tender Lover project, likely involved in its creative or developmental work.
-
B.
Kayah
Kayah is a subgroup of the Karenic branch of the Sino-Tibetan language family, spoken primarily by the Kayah (Karenni) people of Myanmar and neighboring regions.
-
C.
Kwayo
Kwayo is an alternative name for the Kwaio language, an Austronesian language spoken by the Kwaio people of Malaita in the Solomon Islands.
-
D.
Kai
Kai is the fictional half-Japanese, half-English outcast and skilled warrior portrayed by Keanu Reeves in the fantasy samurai film "47 Ronin."
-
E.
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.
- 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_69ca848091c48190bc313d6620d09555 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99ca96a48190a6fbe88387be6883 |
completed | April 1, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1616430808190afbe128d3199bf61 |
completed | April 4, 2026, 7:07 p.m. |
Created at: March 30, 2026, 8:05 p.m.