Triple
T2775444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toni Merkens |
E61557
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Toni |
E150885
|
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: Toni | Statement: [Toni Merkens, givenName, Toni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toni Context triple: [Toni Merkens, givenName, Toni]
-
A.
Toni
chosen
Toni is a common diminutive given name, typically used as a shorter or more familiar form of names like Anton, Anthony, or Antonia.
-
B.
Tina
Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
-
C.
Tina
Tina, formally known as Baroness Stowell of Beeston, is a British Conservative politician and life peer in the House of Lords.
-
D.
Toni Vega
Toni Vega is a musical artist known for contributing featured vocals to tracks such as "Monkey Business."
-
E.
Tiffani
Tiffani is a given name, typically a modern variant of the name Tiffany used for girls.
- 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_69ab4b7cd13481909174bca9809ed259 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd81015481908785fbef0326a2db |
completed | March 7, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc058c8a48190bbd151251678b4ee |
completed | March 10, 2026, 6:55 a.m. |
Created at: March 6, 2026, 9:57 p.m.