Triple
T35118740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Seven-Pointed Star |
E1014111
|
entity |
| Predicate | fictional work |
P119184
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [The Seven-Pointed Star, fictional work, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictional work Context triple: [The Seven-Pointed Star, fictional work, yes]
-
A.
fictionalMaterial
Indicates that something is made of, composed of, or incorporates a material that exists only in fiction or imagination.
-
B.
fictionalType
Indicates that one entity is a fictional or imaginary type or category of the other entity.
-
C.
workInFiction
Indicates that one entity is a fictional work in which the other entity appears or is set.
-
D.
fictionalContent
chosen
Indicates that one entity is content whose subject matter, events, or characters are imaginary or invented rather than factual.
-
E.
fictionalFocus
Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
- F. None of above.
Provenance (3 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_69f76dd8b6948190aaa32b081816bd94 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fee335cb08819097e3a0e09d5ebf49 |
completed | May 9, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69fee2c74fd88190acfc045ab07b7f6b |
completed | May 9, 2026, 7:31 a.m. |
Created at: May 3, 2026, 4:01 p.m.