Triple
T7748063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward Drinker Cope |
E175681
|
entity |
| Predicate | publishedWorksCount |
P6221
|
FINISHED |
| Object | over 1,000 scientific papers and monographs |
—
|
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 1,000 scientific papers and monographs | Statement: [Edward Drinker Cope, publishedWorksCount, over 1,000 scientific papers and monographs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publishedWorksCount Context triple: [Edward Drinker Cope, publishedWorksCount, over 1,000 scientific papers and monographs]
-
A.
numberOfPapers
Indicates the quantity of papers associated with a given entity.
-
B.
yearWorkWritten
Indicates the year in which a particular work was written or created.
-
C.
numberOfWorksCreated
Indicates the total count of creative works that an entity has produced or authored.
-
D.
numberOfWorks
chosen
Indicates the total count of works associated with a given entity.
-
E.
workPublishedBy
Indicates that a work (such as a book, article, or other creation) has been issued or made publicly available by a particular publisher or publishing 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_69c69960b3588190a53aa590d31d9544 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c705257ca08190a78c592a1e616da8 |
completed | March 27, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69c7016df2b08190b2330a2010691431 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:08 p.m.