Triple
T9737357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margareta van Eyck |
E236096
|
entity |
| Predicate | hasSignatureOnPortrait |
P357
|
FINISHED |
| Object | “My husband Jan completed me in the year 1439 on 17 June” |
—
|
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: “My husband Jan completed me in the year 1439 on 17 June” | Statement: [Margareta van Eyck, hasSignatureOnPortrait, “My husband Jan completed me in the year 1439 on 17 June”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignatureOnPortrait Context triple: [Margareta van Eyck, hasSignatureOnPortrait, “My husband Jan completed me in the year 1439 on 17 June”]
-
A.
hasPortrait
Indicates that one entity possesses, displays, or is associated with a portrait depicting another entity.
-
B.
hasSignFor
Indicates that one entity displays, bears, or provides a sign, symbol, or notice that represents, directs attention to, or gives information about another entity.
-
C.
signatureImage
chosen
Indicates that an entity has an associated image that visually represents its signature.
-
D.
hasSign
Indicates that an entity possesses, displays, or is associated with a particular sign or symbol.
-
E.
hasSignatureSmile
Indicates that an entity is characterized by a distinctive or recognizable smile that serves as a notable or identifying feature.
- 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_69ca84d313e88190983ee6ffd0ef60d2 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9ef032088190acd94c35b89e48b7 |
completed | April 1, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69cd03c6ffc88190a5e9569e19122ad5 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:22 p.m.