Triple
T35661696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | coat of arms of Castile and León |
E1030450
|
entity |
| Predicate | colorOfLionField |
P184650
|
FINISHED |
| Object | argent (silver/white) |
—
|
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: argent (silver/white) | Statement: [coat of arms of Castile and León, colorOfLionField, argent (silver/white)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorOfLionField Context triple: [coat of arms of Castile and León, colorOfLionField, argent (silver/white)]
-
A.
clawsColorOfLion
Indicates that a specified color is the color of a lion’s claws.
-
B.
lionColorOnCoatOfArms
Indicates that a lion depicted on a coat of arms has a specified color.
-
C.
maneAndTailColor
Indicates that two entities are related by one having a mane and tail of the specified color.
-
D.
hasFieldMarkingsFor
Indicates that one entity includes or displays field markings that are intended or suitable for use by another entity.
-
E.
colorOfKyrtFields
Indicates the characteristic color associated with Kyrt fields.
- 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_69f76e09f87881909c954aaac176c34f |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b365288c8190bcb11fcfba028737 |
completed | May 3, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69f7b1b8a9fc8190a1279e67a2d12707 |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b2f2b9ac8190aa05b8a1aa18ec2d |
completed | May 3, 2026, 8:41 p.m. |
Created at: May 3, 2026, 4:05 p.m.