Triple
T4132954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | coat of arms of Lorraine |
E85082
|
entity |
| Predicate | tinctureOrdinary |
P54042
|
FINISHED |
| Object | Gules |
—
|
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: Gules | Statement: [coat of arms of Lorraine, tinctureOrdinary, Gules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tinctureOrdinary Context triple: [coat of arms of Lorraine, tinctureOrdinary, Gules]
-
A.
tressureTincture
Indicates the color or pattern (tincture) applied specifically to a tressure in heraldic design.
-
B.
tinctureOfField
Indicates that one entity is a tincture (medicinal extract or solution) derived from, based on, or primarily composed of another entity representing a field or source material.
-
C.
fieldTincture
Indicates the heraldic tincture (color, metal, or fur) applied to the main background field of a coat of arms.
-
D.
chiefTincture
Indicates that one entity serves as the primary or dominant coloring or tonal quality in relation to another entity.
-
E.
tinctureOfLion
Indicates a relationship where something is a medicinal or alchemical preparation (a “tincture”) derived from or associated with a lion.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af01883b6c8190a482ead589a131a5 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af039fb19c8190b20e62a3b3ad25c1 |
completed | March 9, 2026, 5:30 p.m. |
Created at: March 9, 2026, 3:42 p.m.