Triple
T4466784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itaipu Dam |
E98397
|
entity |
| Predicate | recordAnnualGenerationYear |
P56683
|
FINISHED |
| Object | 2016 |
—
|
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: 2016 | Statement: [Itaipu Dam, recordAnnualGenerationYear, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordAnnualGenerationYear Context triple: [Itaipu Dam, recordAnnualGenerationYear, 2016]
-
A.
annualFrom
Indicates that something recurs or is calculated on a yearly basis starting from a specified point in time.
-
B.
averageHouseholdsPoweredPerYear
Indicates the typical number of households that can be supplied with power over the course of one year.
-
C.
recordAttendanceYear
Indicates that an entity’s attendance is recorded or tracked for a specific calendar or academic year.
-
D.
planningYear
Indicates the year in which planning or preparation activities for something are scheduled or designated to occur.
-
E.
yearType
Indicates the classification or category assigned to a specific year (e.g., academic, fiscal, calendar, leap).
- 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_69b3454b4ae481908967426dd37284d6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b356fb69a0819099f0005779f4fcac |
completed | March 13, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69b3563bf4f8819081726cde3a34460b |
completed | March 13, 2026, 12:11 a.m. |
| PDg | Predicate description generation | batch_69b356f9afc48190acb50c45a310e072 |
completed | March 13, 2026, 12:14 a.m. |
Created at: March 12, 2026, 11:34 p.m.