Triple
T9761194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tour First |
E236673
|
entity |
| Predicate | yearOfOriginalCompletion |
P6114
|
FINISHED |
| Object | 1974 |
—
|
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: 1974 | Statement: [Tour First, yearOfOriginalCompletion, 1974]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfOriginalCompletion Context triple: [Tour First, yearOfOriginalCompletion, 1974]
-
A.
originalCompletionYear
chosen
Indicates the year in which something (such as a project, work, or construction) was first fully completed.
-
B.
doctoralDegreeYear
Indicates the calendar year in which an entity received or completed their doctoral degree.
-
C.
workCompletionYear
Indicates the calendar year in which a particular work, project, or task was completed.
-
D.
approximateYearOfCompletion
Indicates the estimated calendar year in which something was completed, rather than an exact or confirmed year.
-
E.
matriculationYear
Indicates the calendar year in which an individual formally enrolled or was admitted into an educational program or institution.
- 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_69ca84d64f6c8190a4ed4e9f5936eda5 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda04ad9008190badfcebe2072ab83 |
completed | April 1, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69cd03d0772c8190bd1750cf1cfba309 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:25 p.m.