Triple
T2526544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Five Ks |
E56046
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Kesh |
E276056
|
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: Kesh | Statement: [Five Ks, hasPart, Kesh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kesh Context triple: [Five Ks, hasPart, Kesh]
-
A.
Kesh
chosen
Kesh is the Sikh practice of maintaining uncut hair, symbolizing spiritual devotion and respect for the natural form given by God.
-
B.
Kes
Kes is a 1969 British drama film directed by Ken Loach, widely acclaimed for its realistic portrayal of a working-class boy in Northern England who finds solace in training a kestrel.
-
C.
Keke
"Keke" is a hip-hop single by rapper Tekashi 6ix9ine, known for its aggressive style and collaboration with fellow New York artists.
-
D.
Kirsha
Kirsha is a central character in Naguib Mahfouz’s novel "Midaq Alley," known as the café owner whose personal life and hidden desires reflect the social and moral tensions of mid-20th-century Cairo.
-
E.
Kors
Kors is the surname of American fashion designer Michael Kors, known for his eponymous luxury brand.
- 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_69ab4a48e4f081908f1218d244608659 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd255f0d081908d20cfb812c4bfc1 |
completed | March 7, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5cf3c790819089b0d202e25e6ede |
completed | March 9, 2026, 11:51 p.m. |
Created at: March 6, 2026, 9:46 p.m.