Triple
T37884981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | coat of arms of the Holy Roman Empire |
E944971
|
entity |
| Predicate | scriptOriginLanguage |
P193810
|
FINISHED |
| Object | Latin |
—
|
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: Latin | Statement: [coat of arms of the Holy Roman Empire, scriptOriginLanguage, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptOriginLanguage Context triple: [coat of arms of the Holy Roman Empire, scriptOriginLanguage, Latin]
-
A.
scriptNameLanguage
Indicates that a script’s name is expressed or written in a particular language.
-
B.
scriptLanguageIdentifier
Indicates the specific programming or scripting language associated with a given script or code artifact.
-
C.
scriptUsedForLanguage
Indicates that a particular writing script is employed to write or represent a given language.
-
D.
indirectOriginLanguage
Indicates that something originates from a particular language, not directly but through one or more intermediate languages or sources.
-
E.
scriptOfOrigin
Indicates that one entity is the original writing system or script from which another script is derived or historically originates.
- 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_69f76ef02668819089e7940c4001af5e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
| PDg | Predicate description generation | batch_69fd553c01488190b9fda48b4a728f04 |
completed | May 8, 2026, 3:15 a.m. |
Created at: May 3, 2026, 4:19 p.m.