Triple
T78852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Zuckerberg |
E1581
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Mark |
E1581
|
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: Mark | Statement: [Mark Zuckerberg, givenName, Mark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Context triple: [Mark Zuckerberg, givenName, Mark]
-
A.
Mark
chosen
Mark is the given name of Mark Zuckerberg, the American technology entrepreneur and co-founder of Facebook.
-
B.
Andrew
Andrew is a masculine given name of Greek origin meaning "manly" or "brave," widely used in English-speaking countries and beyond.
-
C.
Lee
Lee is a given name shared by numerous individuals across different cultures and professions.
-
D.
Carl
Carl is the given name of Carl Sagan, the renowned American astronomer, science communicator, and author.
-
E.
James
James is a common masculine given name of Hebrew origin meaning "supplanter," widely used in English-speaking countries.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24f335b5c8190bf2158d884890ac2 |
completed | Feb. 28, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a25abc7b648190b8a83a05f4c76af0 |
completed | Feb. 28, 2026, 3:02 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.