Triple
T27520943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin Bear |
E694704
|
entity |
| Predicate | heraldicTongueColor |
P74089
|
FINISHED |
| Object | red |
—
|
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: red | Statement: [Berlin Bear, heraldicTongueColor, red]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heraldicTongueColor Context triple: [Berlin Bear, heraldicTongueColor, red]
-
A.
heraldicColor
Indicates that one entity specifies or bears a particular heraldic color in a coat of arms or related heraldic context.
-
B.
heraldicTinctureRed
chosen
Indicates that an entity in a heraldic context is colored or depicted with the red tincture (gules).
-
C.
turtleColorOnCoatOfArms
Indicates that a coat of arms features a turtle of a specified color as part of its heraldic design.
-
D.
heraldicName
Indicates the formal name or designation assigned to a heraldic element (such as a coat of arms, charge, or symbol) within a heraldic system.
-
E.
hasHeraldicMeaning
Indicates that something (typically a symbol, color, or design) carries a specific meaning or significance within the system of heraldry.
- 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_69ef538550208190aa9de8e2cb260d93 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f6383625cc8190aa223d8ef655743c |
completed | May 2, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69f63709e4848190b5cf322e06b23fb6 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 1:21 p.m.