Triple
T2861168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albert Brooks |
E63323
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Albert |
E270293
|
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: Albert | Statement: [Albert Brooks, givenName, Albert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Albert Context triple: [Albert Brooks, givenName, Albert]
-
A.
Albert
Albert is the given name of the renowned theoretical physicist Albert Einstein, whose work revolutionized modern physics.
-
B.
Albert
Albert is the given name of Albert A. Michelson, the pioneering physicist known for his precise measurements of the speed of light and the Michelson–Morley experiment.
-
C.
Albert
Albert is the given first name of American actor and singer Gordon MacRae, best known for his roles in classic film musicals like "Oklahoma!" and "Carousel."
-
D.
Albert
Albert is the given name of the 19th-century German-American painter Albert Bierstadt, renowned for his grand landscapes of the American West.
-
E.
Albert
chosen
Albert is a masculine given name of Germanic origin, commonly used in many European languages and 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf8c676c8190ab29f89d50bd09c3 |
completed | March 7, 2026, 8:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b055e0c8088190a0fa67c9c14fc29b |
completed | March 10, 2026, 5:33 p.m. |
Created at: March 6, 2026, 10:02 p.m.