Triple
T807119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Everybody Knows |
E17462
|
entity |
| Predicate | isFrequentlyDescribedAs |
P21265
|
FINISHED |
| Object | dark |
—
|
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: dark | Statement: [Everybody Knows, isFrequentlyDescribedAs, dark]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFrequentlyDescribedAs Context triple: [Everybody Knows, isFrequentlyDescribedAs, dark]
-
A.
oftenDepictedAs
Indicates that one entity is frequently represented or portrayed in the form, appearance, or symbolism of another entity.
-
B.
describedIn
Indicates that information about an entity is contained or documented within a specified source, such as a text, document, or media.
-
C.
describes
Indicates that one entity provides an explanation, representation, or account of another entity or concept.
-
D.
frequentlyDiscussedIn
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
-
E.
hasDescription
Indicates that an entity is associated with a textual description that explains or characterizes it.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ac07fedc8190ab05595f25c1792f |
completed | March 1, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7221c081908068e66fe720f26d |
completed | March 1, 2026, 9:06 p.m. |
| PDg | Predicate description generation | batch_69a4ac0688708190b62ac0a8239ec8c8 |
completed | March 1, 2026, 9:13 p.m. |
Created at: March 1, 2026, 7:38 p.m.