Triple
T34184799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Étienne François de Choiseul |
E876928
|
entity |
| Predicate | spentLaterYearsAt |
P87337
|
FINISHED |
| Object | Chanteloup |
—
|
NE NERFINISHED |
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: Chanteloup | Statement: [Étienne François de Choiseul, spentLaterYearsAt, Chanteloup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spentLaterYearsAt Context triple: [Étienne François de Choiseul, spentLaterYearsAt, Chanteloup]
-
A.
spentFinalYearsAt
Indicates that an entity spent the last period of its life or existence at a particular place or institution.
-
B.
spentLaterLifeAt
chosen
Indicates that an individual resided, worked, or was primarily based at a particular place during the later period of their life.
-
C.
laterTenure
Indicates that one entity’s tenure or term of service occurs after another entity’s tenure or term of service.
-
D.
timeSinceCollege
Indicates the amount of time that has passed since an entity completed or left college.
-
E.
resumptionYear
Indicates the year in which an activity, process, or state that was previously halted starts again.
- 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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7100873e0819081941ca63dad0a0d |
completed | May 3, 2026, 9:06 a.m. |
| PD | Predicate disambiguation | batch_69f70f3c5bfc81908585f52e196dafe5 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:55 a.m.