Triple
T15032376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GPP |
E378383
|
entity |
| Predicate | inUniverseReception |
P116465
|
FINISHED |
| Object | often disliked by users |
—
|
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 disliked by users | Statement: [GPP, inUniverseReception, often disliked by users]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inUniverseReception Context triple: [GPP, inUniverseReception, often disliked by users]
-
A.
inUniverse
Indicates that one entity exists, occurs, or is set within the fictional or conceptual universe defined by another entity.
-
B.
inUniverseOrigin
Indicates that one entity originates from, or has its source within, the fictional universe or setting defined by another entity.
-
C.
inUniverseActivity
Indicates that an activity or event occurs within the fictional universe or narrative world of a work, rather than outside it (e.g., in real life or meta-context).
-
D.
initialReception
Indicates the nature or quality of the first response or reaction something receives when it is introduced or presented.
-
E.
hasReception
Indicates that an entity hosts, includes, or is associated with a reception event (such as a formal gathering or welcoming function).
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e3a7c8819081f26c2435c1bcb2 |
completed | April 15, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:59 a.m.