Triple
T1275739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | coat of arms of Egypt |
E27208
|
entity |
| Predicate | orientationOfEagle |
P3338
|
FINISHED |
| Object | facing dexter (heraldic right) |
—
|
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: facing dexter (heraldic right) | Statement: [coat of arms of Egypt, orientationOfEagle, facing dexter (heraldic right)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orientationOfEagle Context triple: [coat of arms of Egypt, orientationOfEagle, facing dexter (heraldic right)]
-
A.
orientation
Indicates the relative directional alignment or facing of one entity with respect to another or to a reference frame.
-
B.
eagleFaces
chosen
Indicates that an eagle is oriented toward, looking at, or facing another entity or direction.
-
C.
legOrientation
Indicates the relative positioning or directional alignment of an entity’s leg(s) with respect to a reference frame or another object.
-
D.
shaftOrientation
Indicates the directional alignment or angle at which a shaft is positioned or oriented relative to a reference frame or object.
-
E.
lionAttitude
Indicates the nature or disposition of a lion toward another entity or situation.
- 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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c31602b8819087a57e8d390cae7a |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4bee0be808190a8ccac6a41851fdd |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.