Triple
T6788062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byzantine province of Palaestina Prima |
E155861
|
entity |
| Predicate | laterGovernorTitle |
P1893
|
FINISHED |
| Object | consularis |
—
|
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: consularis | Statement: [Byzantine province of Palaestina Prima, laterGovernorTitle, consularis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterGovernorTitle Context triple: [Byzantine province of Palaestina Prima, laterGovernorTitle, consularis]
-
A.
governorTitle
chosen
Indicates the official title or designation held by a person serving as a governor.
-
B.
provinceGovernor
Indicates that one entity serves as the governor or chief administrative authority of a particular province in relation to the other entity.
-
C.
servedAsGovernorUntil
Indicates that an entity held the position of governor up to a specified end date or time.
-
D.
hadGovernor
Indicates that an administrative region or political entity was governed by a specific person who held the office of governor.
-
E.
governorAfterElection
Indicates that one entity serves as the governor of a region or jurisdiction following a specified election event.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2aa2e0c8190b994261826ae001d |
completed | March 27, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d0979ce0819094678896da4e3169 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:14 p.m.