Triple
T7518610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abraham Silberschatz |
E177707
|
entity |
| Predicate | notableWorkEditionCount |
P6584
|
FINISHED |
| Object | multiple editions of Database System Concepts |
—
|
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: multiple editions of Database System Concepts | Statement: [Abraham Silberschatz, notableWorkEditionCount, multiple editions of Database System Concepts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableWorkEditionCount Context triple: [Abraham Silberschatz, notableWorkEditionCount, multiple editions of Database System Concepts]
-
A.
numberOfEditions
chosen
Indicates the total count of distinct editions associated with a given entity.
-
B.
notableEditionYear
Indicates the year in which a particular edition of something (such as a work, product, or publication) is considered notable or significant.
-
C.
numberOfWorks
Indicates the total count of works associated with a given entity.
-
D.
notableEdition
Indicates that a particular edition or version of a work is especially significant or noteworthy in relation to that work.
-
E.
numberOfWorksCreated
Indicates the total count of creative works that an entity has produced or authored.
- 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_69c69f2891148190a484f3b8222c6f1b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5f850c081909e697219071293fc |
completed | March 27, 2026, 9:26 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d44e9481909813e073b194f6f4 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:46 p.m.