Triple
T26853552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telmarines |
E676120
|
entity |
| Predicate | attitudeTowardTalkingAnimals |
P161999
|
FINISHED |
| Object | oppressive |
—
|
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: oppressive | Statement: [Telmarines, attitudeTowardTalkingAnimals, oppressive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attitudeTowardTalkingAnimals Context triple: [Telmarines, attitudeTowardTalkingAnimals, oppressive]
-
A.
speciesAttitude
Indicates the general disposition, behavior, or stance that one species characteristically holds toward another species or group.
-
B.
featuresTalkingAnimals
Indicates that the subject includes or depicts animals that can speak or communicate using human language.
-
C.
regardsDogsAs
Indicates that one entity holds a particular attitude, view, or treatment toward dogs.
-
D.
animalTypeLoved
Indicates that one entity loves or is especially fond of animals of a particular type.
-
E.
hasAnthropomorphicAnimals
Indicates that something features animals with human-like characteristics, behaviors, or roles.
- 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_69eee9b9d7708190a15d7485709ae981 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f622abdfac8190988421c946411d7e |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f621c7d3e0819095b1f327637ae4f9 |
completed | May 2, 2026, 4:09 p.m. |
Created at: April 27, 2026, 5:19 a.m.