Triple
T20527485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 Florida gubernatorial election |
E503974
|
entity |
| Predicate | recountOccurred |
P140435
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [2018 Florida gubernatorial election, recountOccurred, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recountOccurred Context triple: [2018 Florida gubernatorial election, recountOccurred, true]
-
A.
recount
Indicates that an entity narrates or describes past events or experiences, often in a detailed or sequential manner, to another entity.
-
B.
recountLocation
Indicates that an entity narrates or describes events or experiences associated with a particular location.
-
C.
recountsYearOfEvent
Indicates that an entity provides or narrates the specific year in which a particular event occurred.
-
D.
recordEvent
Indicates that an entity logs or stores information about a specific occurrence or action as an event.
-
E.
occurredDuring
Indicates that one event or action took place within the temporal span of another event or time period.
- 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a0677018819085396cc8795a34e9 |
completed | April 20, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:37 a.m.