Triple
T8067097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicholas Berggruen |
E188270
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nicholas |
E28979
|
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: Nicholas | Statement: [Nicholas Berggruen, givenName, Nicholas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicholas Context triple: [Nicholas Berggruen, givenName, Nicholas]
-
A.
Nicholas
chosen
Nicholas is a masculine given name of Greek origin, commonly used in many cultures and historically borne by numerous saints, rulers, and notable figures.
-
B.
Nicholas Francis
Nicholas Francis is a Danish software developer and entrepreneur best known as a co-founder of the game engine and technology company Unity Technologies.
-
C.
Nicholas Herrick
Nicholas Herrick was the father of the 17th-century English lyric poet and cleric Robert Herrick.
-
D.
Rupert
Rupert is a masculine given name of Germanic origin, commonly used in English-speaking countries and borne by various notable figures.
-
E.
Rupert
Rupert is a small town located in Greenbrier County in the state of West Virginia, United States.
- 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_69ca82b42674819086840efea12478e5 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ff75d208190b7c53d2fe55878ac |
completed | March 31, 2026, 3:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63e587908190980f1f026f4aa153 |
completed | April 1, 2026, 12:16 a.m. |
Created at: March 30, 2026, 5:26 p.m.