Triple
T110166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life and Voyages of Christopher Columbus |
E2229
|
entity |
| Predicate | portrayal |
P1581
|
FINISHED |
| Object | romanticized account of Christopher Columbus |
—
|
LITERAL 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: romanticized account of Christopher Columbus | Statement: [Life and Voyages of Christopher Columbus, portrayal, romanticized account of Christopher Columbus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayal Context triple: [Life and Voyages of Christopher Columbus, portrayal, romanticized account of Christopher Columbus]
-
A.
depicts
chosen
Indicates that one entity visually represents, portrays, or shows another entity.
-
B.
portrayedBy
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
C.
appearance
Indicates how something looks or seems to an observer, including its visible form, condition, or outward impression.
-
D.
depictsPerson
Indicates that one entity visually represents or portrays a specific person.
-
E.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
- F. None of above.
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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a258b58efc8190959c86f73d67b744 |
completed | Feb. 28, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69a25641058c8190b5b64509b35d8176 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.