Triple
T29801239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glendinning family |
E756704
|
entity |
| Predicate | hasWorkAsPartOfSeries |
P88452
|
FINISHED |
| Object | Tales from Benedictine Sources |
—
|
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: Tales from Benedictine Sources | Statement: [Glendinning family, hasWorkAsPartOfSeries, Tales from Benedictine Sources]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkAsPartOfSeries Context triple: [Glendinning family, hasWorkAsPartOfSeries, Tales from Benedictine Sources]
-
A.
hasWorkSeries
chosen
Indicates that one work belongs to, or is part of, a larger series of related works.
-
B.
hasWorkInSameSeries
Indicates that two works belong to and are part of the same series.
-
C.
hasWorkInSeriesRole
Indicates that an entity holds a specific role or function within a particular work that is part of a series.
-
D.
workedOnSeries
Indicates that an entity contributed work to the creation or production of a particular series.
-
E.
worksInSeriesWith
Indicates that one entity collaborates or participates together with another entity within the same series or serialized 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_69f22454583081908927516cb9938d1d |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: April 29, 2026, 5:18 p.m.