Triple
T26177823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voyage en Sardaigne |
E654589
|
entity |
| Predicate | hasTravelNarrativeContent |
P11859
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Voyage en Sardaigne, hasTravelNarrativeContent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTravelNarrativeContent Context triple: [Voyage en Sardaigne, hasTravelNarrativeContent, yes]
-
A.
hasNarrative
chosen
Indicates that one entity contains, presents, or is associated with a story or narrative about another entity or subject.
-
B.
traveledAs
Indicates that an entity moved from one place to another in the role, capacity, or identity specified by another entity (e.g., as a tourist, as a representative, as a refugee).
-
C.
settingOfTravels
Indicates that a location serves as the setting or backdrop for a character’s travels or journey.
-
D.
travelledExtensivelyIn
Indicates that an entity has spent a significant amount of time visiting many places within a particular location or region.
-
E.
hasPerilousAdventure
Indicates that an entity experiences, undertakes, or is involved in a dangerous or high-risk adventure.
- 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_69ee5b45873c81909499203612d05d07 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
Created at: April 26, 2026, 8:38 p.m.