Triple
T31091228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbara FitzRoy |
E792390
|
entity |
| Predicate | spentLifeIn |
P14893
|
FINISHED |
| Object | religious seclusion |
—
|
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: religious seclusion | Statement: [Barbara FitzRoy, spentLifeIn, religious seclusion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spentLifeIn Context triple: [Barbara FitzRoy, spentLifeIn, religious seclusion]
-
A.
spentMostOfLifeIn
Indicates that an entity resided or was primarily based in a particular place for the majority of its lifetime.
-
B.
hasPartInLife
Indicates that an entity participates in, contributes to, or plays a role within some aspect or period of another entity’s life.
-
C.
spentLaterLifeAt
Indicates that an individual resided, worked, or was primarily based at a particular place during the later period of their life.
-
D.
spentEntireCareerWith
Indicates that an individual has worked exclusively for a single organization or team for the full duration of their professional career.
-
E.
spentTimeIn
chosen
Indicates that an entity has spent a certain amount or period of time in a particular place or context.
- 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_69f224ce48348190bd0fc23f656ed683 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69dfdda708190be290c7bec205445 |
completed | May 3, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:02 p.m.