Triple
T5088733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 10 (1950) |
E114700
|
entity |
| Predicate | hasSurfaceQuality |
P60649
|
FINISHED |
| Object | thinly layered paint |
—
|
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: thinly layered paint | Statement: [No. 10 (1950), hasSurfaceQuality, thinly layered paint]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurfaceQuality Context triple: [No. 10 (1950), hasSurfaceQuality, thinly layered paint]
-
A.
hasSurfaceAccuracy
Indicates that one entity possesses a specified degree or measure of accuracy related to its surface characteristics or representation.
-
B.
hasPrimarySurface
Indicates that one entity serves as the main or principal surface associated with another entity.
-
C.
hasSurfaceComposition
Indicates that one entity has a surface made up of, or characterized by, the material or composition specified by another entity.
-
D.
hasQualityCriterion
Indicates that something is associated with a specific standard or criterion used to judge its quality.
-
E.
hasSurfaceSections
Indicates that an entity is composed of or divided into distinct sections or parts of its surface.
- 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_69bd443e941881908eb4e8c685b6f656 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd753f6544819090c028b34ee87536 |
completed | March 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69bd715c0a448190afc837c6c31dc6ab |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd72b8d7a88190ad53fae64f17e22c |
completed | March 20, 2026, 4:15 p.m. |
Created at: March 20, 2026, 1:40 p.m.