Triple
T6775540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gwenn-ha-du |
E155144
|
entity |
| Predicate | hasCantonSymbol |
P50698
|
FINISHED |
| Object | ermine spots |
—
|
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: ermine spots | Statement: [Gwenn-ha-du, hasCantonSymbol, ermine spots]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCantonSymbol Context triple: [Gwenn-ha-du, hasCantonSymbol, ermine spots]
-
A.
cantonSymbol
chosen
Indicates that one entity serves as the official symbol or emblem representing a particular canton.
-
B.
hasCanton
Indicates that an entity is administratively divided into, or associated with, a specific canton.
-
C.
bottomRightCantonSymbol
Indicates that a symbol is located in the bottom-right canton (quarter) of a divided field or flag.
-
D.
topLeftCantonSymbol
Indicates that the specified symbol appears in the top-left canton (corner section) of a flag or similar rectangular field.
-
E.
hasNationalSymbol
Indicates that an entity possesses or is associated with an officially recognized national symbol of a country or nation.
- 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_69c68812ef7c819099369f51febb725c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d24f77c88190be21cf4ef132aa31 |
completed | March 27, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:13 p.m.