Triple
T2591462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lavender Mist (Number 1, 1950) |
E58129
|
entity |
| Predicate | hasNoConventionalFocalPoint |
P40590
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Lavender Mist (Number 1, 1950), hasNoConventionalFocalPoint, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoConventionalFocalPoint Context triple: [Lavender Mist (Number 1, 1950), hasNoConventionalFocalPoint, true]
-
A.
hasFocalPlane
Indicates that an optical system or imaging device possesses a specific focal plane where light is brought into focus.
-
B.
hasNotableCenter
Indicates that an entity possesses a significant or distinguished central location, facility, or hub associated with it.
-
C.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
D.
hasNoDepictionOf
Indicates that the subject lacks any visual or graphical representation of the specified object or concept.
-
E.
hasFocalRatioRange
Indicates that an entity is associated with a range of possible focal ratios, specifying the minimum and maximum f-number values it can have.
- 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd425851c819088db89713c07056f |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d19308819089ee942513d567a4 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd37ef248819090ab6b86b67e355f |
completed | March 7, 2026, 7:27 a.m. |
Created at: March 6, 2026, 9:49 p.m.