Triple
T12874526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Simic |
E307930
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Charles Simic |
E307930
|
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: Charles Simic | Statement: [Charles Simic, name, Charles Simic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charles Simic Context triple: [Charles Simic, name, Charles Simic]
-
A.
Charles Simic
chosen
Charles Simic was a Serbian-American poet, essayist, and translator renowned for his surreal, darkly humorous verse and for serving as the 15th Poet Laureate of the United States.
-
B.
Frank Bidart
Frank Bidart is an acclaimed American poet known for his psychologically intense, formally inventive work that has earned him major literary honors, including the National Book Award for Poetry.
-
C.
Yusef Komunyakaa
Yusef Komunyakaa is an acclaimed American poet known for his jazz-influenced style and powerful explorations of race, memory, and the Vietnam War.
-
D.
Charles Bernstein
Charles Bernstein is an American composer best known for his film scores, particularly his iconic horror music.
-
E.
Doug Mahon
Doug Mahon is a technology entrepreneur best known as a founder of the data storage company Seagate Technology.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970f97f9c81908c75259a4cab1d3c |
completed | April 10, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69bb679f88190a1799b73c3f738b6 |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:38 p.m.