Triple
T16152020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carine M. Feyten |
E391934
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Carine M. Feyten |
E391934
|
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: Carine M. Feyten | Statement: [Carine M. Feyten, name, Carine M. Feyten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carine M. Feyten Context triple: [Carine M. Feyten, name, Carine M. Feyten]
-
A.
Carine M. Feyten
chosen
Carine M. Feyten is an academic leader and educator who serves as the president and chancellor of Texas Woman's University.
-
B.
Barbara Schellekens
Barbara Schellekens is known primarily as the spouse of Gerard de Kremer, better known as the Flemish cartographer and geographer Gerardus Mercator.
-
C.
Judith G. Voet
Judith G. Voet is an American biochemist and textbook author best known for coauthoring the widely used biochemistry textbook "Biochemistry" with Donald Voet.
-
D.
Christine Leunens
Christine Leunens is a New Zealand–based Belgian-American novelist best known for her book "Caging Skies," which was adapted into the Oscar-winning film "Jojo Rabbit."
-
E.
Janine Nabers
Janine Nabers is an American playwright, television writer, and producer known for her work on series such as Swarm, Watchmen, and Atlanta.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d981950819087fdacc7879dca97 |
completed | April 17, 2026, 11:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7ac6d1c8190a8553ceb5ec06119 |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5:01 a.m.