Triple
T19238578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philistine bichrome pottery |
E481066
|
entity |
| Predicate | hasPaint |
P70677
|
FINISHED |
| Object | iron-oxide red 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: iron-oxide red paint | Statement: [Philistine bichrome pottery, hasPaint, iron-oxide red paint]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPaint Context triple: [Philistine bichrome pottery, hasPaint, iron-oxide red paint]
-
A.
isPainted
Indicates that one entity has applied paint to cover or decorate the surface of another entity.
-
B.
hasPaintShop
Indicates that an entity operates, contains, or is associated with a paint shop facility or service.
-
C.
paintedIn
Indicates that an artwork or object was created or executed using paint within a specific time period or at a particular location.
-
D.
paintedOn
chosen
Indicates that one entity has been applied as paint onto the surface of another entity.
-
E.
paintsFor
Indicates that one entity creates paintings or artwork on behalf of, or under commission from, another entity.
- 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_69d8e8ccb8f48190ad420098e74fb1db |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5faef827c81909157bbcd4060dfc9 |
completed | April 20, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e4dcfae6f081909cc173cf71a5005c |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:26 p.m.