Triple
T21386416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Donaldson |
E527511
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Mark |
—
|
NE NERFINISHED |
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: Mark | Statement: [Mark Donaldson, givenName, Mark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Context triple: [Mark Donaldson, givenName, Mark]
-
A.
Mark
chosen
Mark is the first name of Mark Cuban, the American billionaire entrepreneur and owner of the NBA’s Dallas Mavericks.
-
B.
Mark
Mark is the introspective teenage protagonist of the film "As You Are," whose complex friendships and struggles with identity drive the story’s emotional core.
-
C.
Mark
The Mark was the basic unit of currency used in Germany during various historical periods, including the era of the Papiermark.
-
D.
Mark
Mark is a quirky, music-obsessed employee at the independent record store in the 1995 cult film "Empire Records," known for his goofy charm and laid-back attitude.
-
E.
Mark
Mark refers to the historic Margraviate of Brandenburg, a key principality of the Holy Roman Empire that later formed the core territory of Brandenburg-Prussia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0f3d37c8190b43ec77cdb1904c8 |
completed | April 22, 2026, 11:28 a.m. |
Created at: April 16, 2026, 5:12 p.m.