Triple
T4458230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pamela Anderson |
E98183
|
entity |
| Predicate | numberOfPlayboyCovers |
P56644
|
FINISHED |
| Object | more than 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: more than 10 | Statement: [Pamela Anderson, numberOfPlayboyCovers, more than 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPlayboyCovers Context triple: [Pamela Anderson, numberOfPlayboyCovers, more than 10]
-
A.
eraCovered
Indicates that one entity temporally encompasses, includes, or spans the historical period or era associated with another entity.
-
B.
notableCover
Indicates that one entity is a particularly well-known or significant cover version or adaptation of another entity.
-
C.
numberOfSaturdayEveningPostCovers
Indicates the number of times an entity has appeared on the cover of The Saturday Evening Post.
-
D.
ownedBroadsheet
Indicates that one entity possessed ownership of a broadsheet (such as a large-format newspaper or printed sheet).
-
E.
hasCoverArtFeaturing
Indicates that one entity’s cover art visually features or depicts another entity.
- F. None of above. chosen
Provenance (4 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_69b3454a7c608190944f5455c8031d73 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3564485688190a0d49fdccf8724be |
completed | March 13, 2026, 12:11 a.m. |
| PD | Predicate disambiguation | batch_69b34f649df081909d3cc2f6a1b8f282 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b354e1f0948190b645096b2b7037af |
completed | March 13, 2026, 12:05 a.m. |
Created at: March 12, 2026, 11:33 p.m.