Triple
T2608909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | papal coat of arms of Pope Francis |
E58727
|
entity |
| Predicate | hasFieldTincture |
P23234
|
FINISHED |
| Object | azure |
—
|
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: azure | Statement: [papal coat of arms of Pope Francis, hasFieldTincture, azure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFieldTincture Context triple: [papal coat of arms of Pope Francis, hasFieldTincture, azure]
-
A.
fieldTincture
chosen
Indicates the heraldic tincture (color, metal, or fur) applied to the main background field of a coat of arms.
-
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.
featuresTincture
Indicates that something displays or bears a particular tincture (heraldic color, metal, or pattern) as one of its visual characteristics.
-
D.
tressureTincture
Indicates the color or pattern (tincture) applied specifically to a tressure in heraldic design.
-
E.
shieldTincture
Indicates the heraldic color, pattern, or material applied to the surface of a shield.
- 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8def9bc8190b2e013abffc7b191 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd80ab7248190ba06ba14fe4c5638 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:49 p.m.