Triple
T17358552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Markéta Pekarová Adamová |
E422007
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Markéta |
—
|
NE ONNED1 |
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: Markéta | Statement: [Markéta Pekarová Adamová, givenName, Markéta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Markéta Context triple: [Markéta Pekarová Adamová, givenName, Markéta]
-
A.
Markéta
chosen
Markéta is a common Czech female given name, equivalent to Margaret in English.
-
B.
Martina
Martina was a Byzantine empress and the second wife of Emperor Heraclius, known for her controversial influence at court and her role in the empire’s turbulent 7th-century politics.
-
C.
Martina
Martina is a feminine given name of Latin origin, commonly used in many European and Spanish-speaking countries.
-
D.
Arleta
Arleta is a residential neighborhood in the San Fernando Valley region of Los Angeles, California.
-
E.
Markéta Irglová
Markéta Irglová is a Czech singer-songwriter, pianist, and actress best known for co-starring in the film "Once" and winning the Academy Award for Best Original Song for "Falling Slowly."
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a4a37788190b330b7207aa424b6 |
completed | April 19, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01955e4cb481909e3193439bb85cd8 |
in_progress | May 11, 2026, 8:37 a.m. |
Created at: April 10, 2026, 5:44 a.m.