Triple
T6320689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hugo Award for Best Dramatic Presentation |
E141728
|
entity |
| Predicate | splitYear |
P30165
|
FINISHED |
| Object | 2003 |
—
|
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: 2003 | Statement: [Hugo Award for Best Dramatic Presentation, splitYear, 2003]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: splitYear Context triple: [Hugo Award for Best Dramatic Presentation, splitYear, 2003]
-
A.
divisionYear
chosen
Indicates the year in which a division or split of an entity took place.
-
B.
separationYear
Indicates the year in which two entities ended or dissolved their relationship or association.
-
C.
recastInYear
Indicates that an existing work, role, or production was cast again with different performers in a specified year.
-
D.
banYear
Indicates the year in which a ban was enacted or came into effect on the related entity or activity.
-
E.
sharesYearNumberingWith
Indicates that two calendar systems or date representations use the same numbering for years, so a given year has the same numeric label in both.
- 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_69c008d13b8c8190be47d896eb735605 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064c61f008190b316b9ff1023b057 |
completed | March 22, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69c060e5efc48190861b8266e5b0cc0c |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:29 p.m.