Triple
T13545873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal 88 |
E323507
|
entity |
| Predicate | hasGenerationCountApprox |
P8002
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Royal 88, hasGenerationCountApprox, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenerationCountApprox Context triple: [Royal 88, hasGenerationCountApprox, 10]
-
A.
generationCount
chosen
Indicates the number of times a process, entity, or version has been created, iterated, or regenerated within a sequence or lifecycle.
-
B.
hasApproximateEntryCount
Indicates that an entity is associated with a number representing an estimated or non-exact count of its entries.
-
C.
hasApproximateBrickCount
Indicates that an entity is associated with an estimated or non-exact number of bricks.
-
D.
hasGenerationRelationship
Indicates that one entity is involved in producing, creating, or giving rise to another entity.
-
E.
hasApproximateMemberCount
Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae13bec4819084c1770638c00ed9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:45 p.m.