Triple
T7117994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Bartlett |
E165868
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | KB |
E7657
|
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: KB | Statement: [Kevin Bartlett, nickname, KB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KB Context triple: [Kevin Bartlett, nickname, KB]
-
A.
KB
chosen
KB is a distinct entity from Kt, likely representing a separate concept, object, or identifier within the same domain.
-
B.
k_B
k_B is the conventional symbol used to denote the Boltzmann constant, a fundamental physical constant that relates temperature to energy at the particle level.
-
C.
KN
KN is the IATA airline designator assigned to China United Airlines, a Chinese domestic carrier based in Beijing.
-
D.
K
K is the line designation used for Los Angeles Metro's K Line light rail service.
-
E.
K
K is the replicant blade runner protagonist of the science fiction film "Blade Runner 2049," whose investigation into a long-buried secret drives the movie’s central mystery and themes of identity.
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e618bdac8190be291468b7d977bb |
completed | March 27, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79cc2bf2081908e912f26f29394bf |
completed | March 28, 2026, 9:17 a.m. |
Created at: March 27, 2026, 2:43 p.m.