Triple
T13205218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allgemeine Deutsche Biographie |
E314341
|
entity |
| Predicate | numberOfMainVolumes |
P2734
|
FINISHED |
| Object | 55 |
—
|
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: 55 | Statement: [Allgemeine Deutsche Biographie, numberOfMainVolumes, 55]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMainVolumes Context triple: [Allgemeine Deutsche Biographie, numberOfMainVolumes, 55]
-
A.
numberOfVolumes
chosen
Indicates the total count of separate volumes or parts that make up a multi-volume work or collection.
-
B.
numberOfMainElements
Indicates the quantity of primary or central elements associated with an entity or structure.
-
C.
hasThreeVolumeStructureRole
Indicates that an entity participates in or fulfills a role within a three-volume structural organization or framework.
-
D.
numberOfPrimaryMirrorSegments
Indicates the total count of individual segments that make up a system’s primary mirror.
-
E.
numberOfMainHouses
Indicates the quantity of primary or main residential houses associated with an 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c9b0cf08190a1d71cc94139539d |
completed | April 10, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69d98bc938f081909f123bdf1263ff7f |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:17 p.m.