Triple
T13370758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | York Factory |
E319051
|
entity |
| Predicate | receivedGoods |
P4382
|
FINISHED |
| Object | European manufactured goods |
—
|
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: European manufactured goods | Statement: [York Factory, receivedGoods, European manufactured goods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receivedGoods Context triple: [York Factory, receivedGoods, European manufactured goods]
-
A.
receivedDocument
Indicates that one entity has been given and taken possession of a document from another entity or source.
-
B.
receivedFor
Indicates that something was obtained, accepted, or taken into possession on behalf of or for the benefit of a specified entity.
-
C.
receivedForWork
Indicates that something was obtained or accepted as compensation or reward in exchange for performing work or services.
-
D.
receivedRedress
Indicates that an entity has been given compensation, remedy, or corrective action in response to a prior harm, grievance, or injustice.
-
E.
receives
chosen
Indicates that one entity is the recipient of something (such as an object, message, or action) from another entity.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcd8950481909785a2060f43b6ed |
completed | April 11, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69d9a02c9abc8190b328e7bae747bfc5 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:33 p.m.