Triple
T3747790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian tricolour naval ensign |
E81248
|
entity |
| Predicate | scriptOnEmblem |
P34700
|
FINISHED |
| Object | Latin inscription on lion’s book in Venice quarter |
—
|
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 inscription on lion’s book in Venice quarter | Statement: [Italian tricolour naval ensign, scriptOnEmblem, Latin inscription on lion’s book in Venice quarter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptOnEmblem Context triple: [Italian tricolour naval ensign, scriptOnEmblem, Latin inscription on lion’s book in Venice quarter]
-
A.
scriptNameOfEmblem
chosen
Indicates the name of the script or writing system used in the emblem.
-
B.
emblemName
Indicates that a specified name is the official or recognized title of an emblem.
-
C.
symbolOnInsignia
Indicates that a particular symbol appears on or is featured as part of an insignia.
-
D.
scriptOnFlag
Indicates that a script is attached to and/or executed when a specific flag or condition is set.
-
E.
protectiveEmblemName
Indicates that a given name is the designated title or label of a protective emblem associated with an entity or context.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb6ac5ac8190934ec1a6c887a8f5 |
completed | March 8, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69adc04adebc819088d7f36d0ac343a6 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.