Triple
T7610505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milner |
E172222
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Millner |
E183622
|
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: Millner | Statement: [Milner, hasVariant, Millner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Millner Context triple: [Milner, hasVariant, Millner]
-
A.
Millner
chosen
Millner is an English occupational surname historically associated with people who made or sold hats or millinery goods.
-
B.
Millard
Millard is the given name of Millard Fillmore, the 13th president of the United States.
-
C.
Milne
Milne is a Scottish-origin surname most famously associated with A. A. Milne, the English author who created Winnie-the-Pooh.
-
D.
Mankessim
Mankessim is a major commercial and historical town in Ghana known as an important market center and traditional seat of the Fante people.
-
E.
Menzel
Menzel is the surname of Idina Menzel, the American actress and singer best known for her roles in Broadway musicals and the film "Frozen."
- 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_69c6994f50808190ba228764bb422417 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa20ac2c8190ac7ab90b4df406b6 |
completed | March 27, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c868600c7c81909cdeebdb5b2bdaf3 |
completed | March 28, 2026, 11:46 p.m. |
Created at: March 27, 2026, 3:54 p.m.