Triple
T22069880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gruvbyn |
E545375
|
entity |
| Predicate | hasColorTradition |
P31069
|
FINISHED |
| Object | red-painted wooden houses |
—
|
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: red-painted wooden houses | Statement: [Gruvbyn, hasColorTradition, red-painted wooden houses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColorTradition Context triple: [Gruvbyn, hasColorTradition, red-painted wooden houses]
-
A.
hasTraditionalColors
chosen
Indicates that an entity is associated with colors that are traditionally or customarily linked to it.
-
B.
traditionalDressColor
Indicates the color associated with an entity’s traditional or customary dress or clothing.
-
C.
hasHairstyleTradition
Indicates a relationship where an entity follows, practices, or is associated with a particular traditional hairstyle.
-
D.
variantTraditions
Indicates that there exist differing or alternative traditions or customary practices associated with the same subject or context.
-
E.
hasTraditionIn
Indicates that a particular tradition, custom, or longstanding practice is present, observed, or established within a specified place, group, or context.
- 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1288724e881908b38fe7e56d3b448 |
completed | April 28, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69e6f64a6a70819089d1a6c3a2384861 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:28 p.m.