Triple
T1326137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kathleen |
E28330
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Kath |
E151965
|
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: Kath | Statement: [Kathleen, hasVariant, Kath]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kath Context triple: [Kathleen, hasVariant, Kath]
-
A.
Kat
chosen
Kat is a given name, typically used as a shortened or informal form of Kathleen or Katherine.
-
B.
Kathy
Kathy is the given name of Kathy Hochul, the 57th governor of New York and the first woman to hold that office.
-
C.
Kathryn
Kathryn is a feminine given name, commonly considered a variant spelling of Katherine/Catherine.
-
D.
Karen
Karen is a common feminine given name used in many English-speaking and European countries.
-
E.
Karen
The Karen are an indigenous ethnic group of Southeast Asia, primarily living in Myanmar and Thailand, with distinct languages, cultures, and a long history of political struggle and displacement.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19fd2648190932a85eacb3e7ec4 |
completed | March 1, 2026, 10:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acd47471108190b01121b384d871aa |
completed | March 8, 2026, 1:44 a.m. |
Created at: March 1, 2026, 7:55 p.m.