Triple
T13372746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Lady of Sorrows |
E319106
|
entity |
| Predicate | hasTraditionalColor |
P31069
|
FINISHED |
| Object | black |
—
|
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: black | Statement: [Our Lady of Sorrows, hasTraditionalColor, black]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalColor Context triple: [Our Lady of Sorrows, hasTraditionalColor, black]
-
A.
hasTraditionalColors
chosen
Indicates that an entity is associated with colors that are traditionally or customarily linked to it.
-
B.
hasTraditionalSymbol
Indicates that something is associated with or represented by a conventional or culturally established symbol.
-
C.
hasTraditionalName
Indicates that an entity is associated with a name traditionally used or recognized for it, often rooted in long-standing cultural or historical practice.
-
D.
isTraditional
Indicates that something adheres to long-established customs, practices, or norms rather than modern or innovative ones.
-
E.
isColor
Indicates that one entity represents the color attribute or hue of 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcd8950481909785a2060f43b6ed |
completed | April 11, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69d9a02c9abc8190b328e7bae747bfc5 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:33 p.m.