Triple
T18207251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Marriage of Heaven and Hell |
E435938
|
entity |
| Predicate | approximateNumberOfPlates |
P33015
|
FINISHED |
| Object | 27 |
—
|
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: 27 | Statement: [The Marriage of Heaven and Hell, approximateNumberOfPlates, 27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfPlates Context triple: [The Marriage of Heaven and Hell, approximateNumberOfPlates, 27]
-
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.
hasApproximateNumberOfVarieties
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
-
D.
estimatedShellCount
Indicates the estimated number of shells associated with or attributed to an entity.
-
E.
approximateProductionNumber
Indicates that one entity specifies an estimated or non-exact quantity associated with the production output of 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e2243de081908a5bcc7e2072eae7 |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.