Triple
T38659534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mack Mackenzie |
E939990
|
entity |
| Predicate | attendsWith |
P191487
|
FINISHED |
| Object | Daria Morgendorffer |
—
|
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: Daria Morgendorffer | Statement: [Mack Mackenzie, attendsWith, Daria Morgendorffer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attendsWith Context triple: [Mack Mackenzie, attendsWith, Daria Morgendorffer]
-
A.
blendsWith
Indicates that one entity can be mixed or combined smoothly with another to form a uniform or harmonious result.
-
B.
endsWith
Indicates that one entity terminates with, or has as its final part, the sequence or element represented by the other entity.
-
C.
hasEnding
Indicates that one entity concludes with, or terminates in, another entity (such as a specific substring, segment, or final component).
-
D.
endsUpWith
Indicates that, as a result of some process or sequence of events, one entity ultimately comes to possess, receive, or be associated with another entity.
-
E.
hasTypeOfEnding
Indicates that one entity possesses or exhibits a particular kind or category of ending associated with another entity.
- F. None of above. chosen
Provenance (4 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_69f76ede49648190a48bfe47032a05a3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
| PDg | Predicate description generation | batch_69fcdfbafbf48190abe38ec0003a6419 |
completed | May 7, 2026, 6:53 p.m. |
Created at: May 3, 2026, 4:33 p.m.