Triple
T14983525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port de pêche en Bretagne |
E373641
|
entity |
| Predicate | hasCreatorLifeSpan |
P27074
|
FINISHED |
| Object | 1861–1918 |
—
|
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: 1861–1918 | Statement: [Port de pêche en Bretagne, hasCreatorLifeSpan, 1861–1918]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCreatorLifeSpan Context triple: [Port de pêche en Bretagne, hasCreatorLifeSpan, 1861–1918]
-
A.
creatorLifespan
chosen
Indicates the time period between the birth and death of the creator associated with an entity.
-
B.
hasLifetimeStatus
Indicates that an entity is associated with a status or condition that applies for the entire duration of its existence.
-
C.
authorLifespanContext
Indicates the temporal or historical context of an author’s life span in relation to other events, periods, or entities.
-
D.
existsSince
Indicates that an entity has been in existence or valid from a specified point in time onward.
-
E.
authorAgeAtCreation
Indicates the age of an author at the time they created a particular work.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6fe42a081909308f788fdf024d5 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:52 a.m.