Triple
T35286696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rossen |
E1019103
|
entity |
| Predicate | hasNotableWorkViaBearer |
P61425
|
FINISHED |
| Object | All the King's Men |
E823867
|
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: All the King's Men | Statement: [Rossen, hasNotableWorkViaBearer, All the King's Men]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableWorkViaBearer Context triple: [Rossen, hasNotableWorkViaBearer, All the King's Men]
-
A.
hasNotableWorkRights
Indicates that an entity holds legal or recognized rights associated with a notable work, such as authorship, ownership, or usage rights.
-
B.
hasNotableWorkSetThere
Indicates that a notable work (such as a book, film, or other creative piece) is set in or takes place within the referenced location.
-
C.
hasNotableWorkExample
chosen
Indicates that an entity has a specific notable work cited as an example associated with it.
-
D.
hasWorksAbout
Indicates that one entity (such as a creator, collection, or source) includes or is associated with works whose subject or focus is another entity.
-
E.
hasCatalogedWorkOn
Indicates that an entity has formally recorded, listed, or documented another entity as a work within a catalog or collection.
- F. None of above.
Provenance (4 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_69f76de6d39c8190bb11342e4b91ff2b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3823b9225081908968e6650b362cf7 |
completed | June 21, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:03 p.m.