Triple
T1969200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Debate with Robert Owen (1829) |
E42758
|
entity |
| Predicate | hasYearInTitle |
P33319
|
FINISHED |
| Object | 1829 |
—
|
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: 1829 | Statement: [Debate with Robert Owen (1829), hasYearInTitle, 1829]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasYearInTitle Context triple: [Debate with Robert Owen (1829), hasYearInTitle, 1829]
-
A.
hasTypeOfYear
Indicates that a given year is classified as belonging to a specific type or category of year (e.g., fiscal, academic, leap).
-
B.
yearOfPassage
Indicates the specific calendar year in which a law, bill, or formal measure was officially passed or enacted.
-
C.
hadTitle
Indicates that an entity held or was assigned a specific title or formal designation.
-
D.
claimedYear
Indicates the year that is asserted or reported as being associated with an event, status, or fact, regardless of whether it is verified.
-
E.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
- 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_69a88711151c8190940b2572095059d7 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3d05cb88190963039d643bb6637 |
completed | March 7, 2026, 5:12 a.m. |
| PD | Predicate disambiguation | batch_69abaff7d4a48190ab0d51aefb1c4e31 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb16a6db48190af04012e8ed2269f |
completed | March 7, 2026, 5:02 a.m. |
Created at: March 4, 2026, 7:36 p.m.