Triple
T5216290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Flanders |
E117759
|
entity |
| Predicate | tongueTincture |
P62084
|
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 Flanders, tongueTincture, Gules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tongueTincture Context triple: [Coat of arms of Flanders, tongueTincture, Gules]
-
A.
tinctureOfTongueAndClaws
Indicates a condition or effect in which both speech (tongue) and physical attacks (claws) are imbued with a special, often magical or poisonous, potency.
-
B.
tinctureOfLion
Indicates a relationship where something is a medicinal or alchemical preparation (a “tincture”) derived from or associated with a lion.
-
C.
tressureTincture
Indicates the color or pattern (tincture) applied specifically to a tressure in heraldic design.
-
D.
tinctureOrdinary
Indicates that an ordinary (a basic heraldic shape or charge) is depicted with a specific tincture (color, metal, or fur) in a coat of arms.
-
E.
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.
- 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_69bd4464ba3c8190bc16b2ebbe42ddb0 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a93fcc08190a1d2d025b4365d5a |
completed | March 20, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69bd77bb4e8c819094b5ac7cf61512f9 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd79000cf88190b3c05d95395b0cd2 |
completed | March 20, 2026, 4:42 p.m. |
Created at: March 20, 2026, 1:48 p.m.