Triple
T18319459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darley Arabian |
E438830
|
entity |
| Predicate | approximateYearOfImport |
P131356
|
FINISHED |
| Object | 1704 |
—
|
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: 1704 | Statement: [Darley Arabian, approximateYearOfImport, 1704]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateYearOfImport Context triple: [Darley Arabian, approximateYearOfImport, 1704]
-
A.
yearOfManufacture
Indicates the specific calendar year in which an item was produced or manufactured.
-
B.
purchaseYear
Indicates the calendar year in which a purchase or acquisition of something took place.
-
C.
accessionYear
Indicates the calendar year in which an item, record, or entity was formally added to or registered within a collection, system, or institution.
-
D.
yearFirstDelivered
Indicates the calendar year in which something (such as a product, service, or item) was first delivered or made available.
-
E.
yearOfProduction
Indicates the specific year in which an item, work, or product was created or manufactured.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50aa4d3308190883714e1ef6a1d84 |
completed | April 19, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69e44fe4ee10819086b4142444fca1f5 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:36 a.m.