Triple
T2459016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M13 |
E54486
|
entity |
| Predicate | catalogueInclusionYear |
P40626
|
FINISHED |
| Object | 1764 |
—
|
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: 1764 | Statement: [M13, catalogueInclusionYear, 1764]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: catalogueInclusionYear Context triple: [M13, catalogueInclusionYear, 1764]
-
A.
acquisitionAnnouncementYear
Indicates the calendar year in which an acquisition is publicly announced.
-
B.
hasYearInTitle
Indicates that the title of an entity explicitly contains a year value as part of its text.
-
C.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
-
D.
accessionYear
Indicates the calendar year in which an item, record, or entity was formally added to or registered within a collection, system, or institution.
-
E.
modelYears
Indicates the association between a product (often a vehicle or device) and the specific calendar years in which that model version was produced or marketed.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd49c5aa081909ab4f726a458b77f |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0b199488190aa381b36593ae1ac |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd49b5d2481908817aeb171e2bd61 |
completed | March 7, 2026, 7:32 a.m. |
Created at: March 6, 2026, 9:44 p.m.