Triple
T32300659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nova Roma |
E825228
|
entity |
| Predicate | laterCommonName |
P200410
|
FINISHED |
| Object | Constantinople |
—
|
NE NERFINISHED |
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: Constantinople | Statement: [Nova Roma, laterCommonName, Constantinople]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterCommonName Context triple: [Nova Roma, laterCommonName, Constantinople]
-
A.
otherCommonName
Indicates that an entity is known by an additional, alternative common name besides its primary one.
-
B.
lessCommonNameFor
Indicates that the subject is a less commonly used name or label for the same entity or concept as the object.
-
C.
moreCommonPublicName
Indicates that one name is used more frequently or popularly in public contexts than another alternative name for the same entity.
-
D.
commonName
Indicates that one entity is the commonly used or vernacular name by which the other entity is known.
-
E.
commonNameOf
Indicates that one entity is the commonly used or popular name by which the other entity is known.
- 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_69f349115304819084ee91d345b6c8aa |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ff891e4b9c8190aa86a339a8944496 |
completed | May 9, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69ff8801180c8190b23e20996ca68e0a |
completed | May 9, 2026, 7:16 p.m. |
| PDg | Predicate description generation | batch_69ff891d54248190be8742197564605a |
completed | May 9, 2026, 7:21 p.m. |
Created at: May 1, 2026, 12:45 a.m.