Triple
T23246623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asia (Roman province) |
E581599
|
entity |
| Predicate | rankInSenatorialProvinces |
P151526
|
FINISHED |
| Object | first |
—
|
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: first | Statement: [Asia (Roman province), rankInSenatorialProvinces, first]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInSenatorialProvinces Context triple: [Asia (Roman province), rankInSenatorialProvinces, first]
-
A.
rankInStateCouncil
Indicates the position or level an individual holds within a specific state's council hierarchy.
-
B.
senatorialDistrict
Indicates the specific senatorial district to which an entity (such as a person, place, or office) is assigned or associated.
-
C.
hasNumberOfSenatorialDivisions
Indicates the relationship that specifies how many senatorial divisions are associated with a given entity.
-
D.
electoralRank
Indicates the position or level an entity holds within an electoral hierarchy or ranking system.
-
E.
numberOfSenates
Indicates the total count of senate bodies associated with or present in a given context or entity.
- 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f1e8448190b8420a8dc6e24576 |
completed | April 29, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:10 p.m.