Triple
T78881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Zuckerberg |
E1581
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object | Zuck |
E306
|
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: Zuck | Statement: [Mark Zuckerberg, hasNickname, Zuck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zuck Context triple: [Mark Zuckerberg, hasNickname, Zuck]
-
A.
Dwight
Dwight is a masculine given name most famously borne by Dwight D. Eisenhower, the 34th president of the United States and Supreme Allied Commander in World War II.
-
B.
Mark Zuckerberg
chosen
Mark Zuckerberg is an American technology entrepreneur and philanthropist best known as the co-founder and CEO of Facebook (now Meta Platforms).
-
C.
Lee
Lee is a given name shared by numerous individuals across different cultures and professions.
-
D.
Andrew
Andrew is a masculine given name of Greek origin meaning "manly" or "brave," widely used in English-speaking countries and beyond.
-
E.
Rogers
Rogers is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
- 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_69a255522b0081909f8a02667108a6d3 |
completed | Feb. 28, 2026, 2:39 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.