Triple
T740902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Global Innovation Index |
E15240
|
entity |
| Predicate | hasFirstEditionYear |
P19469
|
FINISHED |
| Object | 2007 |
—
|
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: 2007 | Statement: [Global Innovation Index, hasFirstEditionYear, 2007]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstEditionYear Context triple: [Global Innovation Index, hasFirstEditionYear, 2007]
-
A.
firstEditionResult
Indicates that one entity is the outcome, record, or result associated specifically with the first edition of another entity.
-
B.
firstEditionSoldOutTime
Indicates the point in time at which the first edition of an item became completely sold out.
-
C.
firstSeriesYear
Indicates the year in which a series (such as a TV show, book series, or sports league season) first began or was initially released.
-
D.
firstEditionVolumes
Indicates that the subject is a work or publication and the object is the number of volumes in its first edition.
-
E.
wasFirstBuiltInYear
Indicates that the initial construction of an entity was completed in a specified year.
- 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64adf2c81908e48090be35dd9d9 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fc734c81908fbd36386d5746d6 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a64957ec81909fe2e2dbffd80ed3 |
completed | March 1, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:37 p.m.