Triple
T2451371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | H. Rap Brown |
E53711
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Hubert |
E164283
|
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: Hubert | Statement: [H. Rap Brown, givenName, Hubert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hubert Context triple: [H. Rap Brown, givenName, Hubert]
-
A.
Hubert
chosen
Hubert is a masculine given name of Germanic origin meaning "bright heart" or "shining intellect," historically borne by saints, nobles, and notable public figures.
-
B.
Georges
Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
-
C.
Herbert
Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
-
D.
Henri
Henri is a given name most famously associated with the French artist Henri Matisse.
-
E.
Reginald
Reginald is a masculine given name of English origin that has been borne by various notable figures, including military officers, politicians, and artists.
- 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_69ab495d227c8190b26ae6548eeb1019 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd0f52524819088b00009c9dd1823 |
completed | March 7, 2026, 7:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef0c2a7b08190beb27f6a83208e5c |
completed | March 9, 2026, 4:09 p.m. |
Created at: March 6, 2026, 9:43 p.m.