Triple
T5897530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Capshaw |
E131135
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kathleen |
E28330
|
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: Kathleen | Statement: [Kate Capshaw, givenName, Kathleen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kathleen Context triple: [Kate Capshaw, givenName, Kathleen]
-
A.
Kathleen
chosen
Kathleen is a feminine given name of Irish origin, derived from the name Catherine and widely used in English-speaking countries.
-
B.
Kathleen
"Kathleen" is a punk rock song by the American band Pinhead Gunpowder, known for its raw, melodic style and association with the East Bay punk scene.
-
C.
Kathryn
Kathryn is a feminine given name, commonly considered a variant spelling of Katherine/Catherine.
-
D.
Kathy
Kathy is the given name of Kathy Hochul, the 57th governor of New York and the first woman to hold that office.
-
E.
Katherine Murphy
Katherine Murphy is a central character in the romantic comedy film "Just Go with It," where she becomes entangled in a web of lies and pretend relationships that evolve into genuine romance.
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c036f65c1c819084cb90662af6e114 |
completed | March 22, 2026, 6:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b159cb908190b78b78d1e854212b |
completed | March 23, 2026, 3:19 a.m. |
Created at: March 22, 2026, 3:58 p.m.