Triple
T3795052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neil Diamond |
E89749
|
entity |
| Predicate | wroteSong |
P2831
|
FINISHED |
| Object | America |
E287708
|
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: America | Statement: [Neil Diamond, wroteSong, America]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: America Context triple: [Neil Diamond, wroteSong, America]
-
A.
America
America is the landmass in the Western Hemisphere comprising the continents of North and South America, widely recognized for its vast geographic, cultural, and political diversity.
-
B.
America
chosen
"America" is a lively, satirical musical number from *West Side Story* that contrasts the promises and prejudices of life in the United States as debated by Puerto Rican immigrants.
-
C.
America
America was the Command and Service Module spacecraft used on NASA’s Apollo 17 mission, the final crewed lunar landing of the Apollo program.
-
D.
America
"America" is a seminal and politically charged Judge Dredd storyline that explores themes of democracy, authoritarianism, and personal freedom within the dystopian world of Mega-City One.
-
E.
Amerika
Amerika is a novel by Franz Kafka that follows a young European immigrant’s surreal and often absurd experiences in the 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_69aed9597d6881909b6ee3b9de859223 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee79db2e88190b3aa2b8e8d885e19 |
completed | March 9, 2026, 3:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f0c294881908a69addadb7b2d98 |
completed | March 14, 2026, 3:30 p.m. |
Created at: March 9, 2026, 3:15 p.m.