Triple
T18444095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bacchylides |
E450610
|
entity |
| Predicate | numberOfSurvivingFragments |
P20105
|
FINISHED |
| Object | numerous fragments |
—
|
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: numerous fragments | Statement: [Bacchylides, numberOfSurvivingFragments, numerous fragments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSurvivingFragments Context triple: [Bacchylides, numberOfSurvivingFragments, numerous fragments]
-
A.
numberOfSurvivingSpecimens
Indicates the count of individual specimens that remain alive or intact after a particular event, period, or condition.
-
B.
survivingPortions
Indicates that certain parts or segments of something remain intact or extant after other portions have been lost, destroyed, or removed.
-
C.
numberOfFragmentsApprox
chosen
Indicates an approximate count of how many fragments or pieces are associated with the subject.
-
D.
numberOfSurvivingTakes
Indicates the count of takes or attempts that successfully remained valid or usable after others were discarded or failed.
-
E.
numberOfSurvivingPlays
Indicates the count of plays by an author or in a collection that are still extant rather than lost.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c142abc8190b4f6f938acdc413d |
completed | April 19, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:30 a.m.