Triple
T32933090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bobbsey family |
E842448
|
entity |
| Predicate | hasTwinSet |
P114679
|
FINISHED |
| Object | Bert Bobbsey |
—
|
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: Bert Bobbsey | Statement: [Bobbsey family, hasTwinSet, Bert Bobbsey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTwinSet Context triple: [Bobbsey family, hasTwinSet, Bert Bobbsey]
-
A.
hasTwin
Indicates that one entity is a twin of another, sharing the same birth event or time with a sibling.
-
B.
hasTwinStatus
chosen
Indicates that an entity has a twin relationship or classification, such as being one of a pair of twins or having an associated twin counterpart.
-
C.
hasTwinCharacters
Indicates that two characters are twins, sharing the same parents and birth time or very close birth times.
-
D.
isTwinWith
Indicates that two entities are twins, sharing the same birth parents and being born at (or very near) the same time.
-
E.
hasTwinSatellite
Indicates that one celestial body possesses a satellite that is paired with another satellite in a twin or closely matched relationship.
- 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_69f34948adfc8190a937f1f622783c0b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d10722e88190bb59c5768ce23d43 |
completed | May 3, 2026, 4:37 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe5f93c8190995c53dbbe380a32 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:20 a.m.