Triple
T10115329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy Drew series |
E218341
|
entity |
| Predicate | numberOfVolumesApproximate |
P2734
|
FINISHED |
| Object | over 170 |
—
|
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: over 170 | Statement: [Nancy Drew series, numberOfVolumesApproximate, over 170]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfVolumesApproximate Context triple: [Nancy Drew series, numberOfVolumesApproximate, over 170]
-
A.
numberOfVolumes
chosen
Indicates the total count of separate volumes or parts that make up a multi-volume work or collection.
-
B.
approximateVolumeInCubicCentimetres
Indicates that one entity has an estimated or roughly calculated volume measured in cubic centimetres.
-
C.
hasEstimatedOriginalVolume
Indicates that an entity is associated with an approximate or calculated value for its original volume.
-
D.
hasLargeVolume
Indicates that an entity possesses or is characterized by a comparatively large physical or quantitative volume.
-
E.
hasApproximateVendorCount
Indicates that an entity is associated with an estimated or non-exact number of vendors.
- 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd161831c81908bb3c77caa7c3ce1 |
completed | April 2, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9ed7e48190aa132ef8a69b49f9 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:04 p.m.