Triple
T7226327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MKT |
E154788
|
entity |
| Predicate | nicknameOf |
P744
|
FINISHED |
| Object | the Katy |
E154789
|
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: the Katy | Statement: [MKT, nicknameOf, the Katy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: the Katy Context triple: [MKT, nicknameOf, the Katy]
-
A.
Katy
Katy is a common feminine given name, typically used as a diminutive form of Katherine or similar names.
-
B.
Katy
chosen
Katy is the popular nickname for the Missouri–Kansas–Texas Railroad, a historic American railway that served the central and southern United States.
-
C.
Katy
Katy is a tough, sharp-witted woman from the Canadian comedy series "Letterkenny," known for being Wayne’s sister and a core member of the show’s central friend group.
-
D.
Kinkaid
Kinkaid is a surname of English and Scottish origin borne by various notable individuals, including military figures and public officials.
-
E.
Katy Flyer
The Katy Flyer was a prominent passenger train that operated in the central United States, serving key routes of the Missouri–Kansas–Texas Railroad during the early to mid-20th century.
- 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_69c68811dd1c8190ac460bb39e64e1f0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6e9de21e081908f30700f6211c5ef |
completed | March 27, 2026, 8:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7d38686ac819098705463a65dec87 |
completed | March 28, 2026, 1:11 p.m. |
Created at: March 27, 2026, 2:54 p.m.