Triple
T10642219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron de Wolmar |
E250749
|
entity |
| Predicate | readerReception |
P95128
|
FINISHED |
| Object | often criticized as cold and inhuman |
—
|
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: often criticized as cold and inhuman | Statement: [Baron de Wolmar, readerReception, often criticized as cold and inhuman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readerReception Context triple: [Baron de Wolmar, readerReception, often criticized as cold and inhuman]
-
A.
readingExperience
Indicates the relationship in which an entity engages with written or visual material, capturing the act, manner, or quality of that reading activity.
-
B.
readership
Indicates the relationship in which one party reads, follows, or is the audience for the written or published work of another.
-
C.
reading
Indicates that an entity is engaged in the activity of interpreting and understanding written or printed material from another entity or source.
-
D.
readingSystem
Indicates a system or device that presents, interprets, or processes written or digital content for a user.
-
E.
readingFeature
Indicates that an entity possesses a characteristic, capability, or attribute specifically related to reading.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfce1ddc8190893fe6f7b047b56b |
completed | April 8, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69d6dd83b114819098e84dc658e82d7e |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df463ea8819091d6683e476b4f21 |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 9:05 p.m.