Triple
T13790290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Illustrations to Homer’s Odyssey |
E331375
|
entity |
| Predicate | circaNumberOfPlates |
P33015
|
FINISHED |
| Object | approximately 34 plates |
—
|
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: approximately 34 plates | Statement: [Illustrations to Homer’s Odyssey, circaNumberOfPlates, approximately 34 plates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: circaNumberOfPlates Context triple: [Illustrations to Homer’s Odyssey, circaNumberOfPlates, approximately 34 plates]
-
A.
numberOfPlates
chosen
Indicates the quantity of plates associated with or involved in a particular entity, event, or context.
-
B.
plateNumberOf
Indicates the license plate number that is assigned to or associated with a particular vehicle.
-
C.
numberOfRevolvingRestaurants
Indicates the quantity of revolving restaurants associated with or contained within a given entity.
-
D.
estimatedShellCount
Indicates the estimated number of shells associated with or attributed to an entity.
-
E.
numberOfCups
Indicates the quantity of cups associated with a given entity or context.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de024af32c8190a9bd1278e09564ba |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbc85fb600819098a2aab48169be96 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:11 p.m.