Triple
T16992249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Office of the Mayor of Atlanta |
E412220
|
entity |
| Predicate | officeHolderTermLimit |
P541
|
FINISHED |
| Object | two consecutive terms |
—
|
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: two consecutive terms | Statement: [Office of the Mayor of Atlanta, officeHolderTermLimit, two consecutive terms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderTermLimit Context triple: [Office of the Mayor of Atlanta, officeHolderTermLimit, two consecutive terms]
-
A.
termLimitDefinedBy
chosen
Indicates that the duration or number of terms for holding a position is specified or constrained by a particular rule, law, or authority.
-
B.
incumbentTermLimited
Indicates that the current officeholder is restricted by term limits from serving another consecutive term in that office.
-
C.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
-
D.
officeHoldersNumberLimit
Indicates a constraint specifying the maximum number of individuals who may simultaneously hold a particular office or position.
-
E.
electsTermLength
Indicates the length of time for which an entity is elected to hold a particular position or office.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d283d2388190a78bf8d179e83fdc |
completed | April 18, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.