Triple
T26197971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juan |
E655157
|
entity |
| Predicate | commonCompoundName |
P85414
|
FINISHED |
| Object | Juan Carlos |
—
|
NE NERFINISHED |
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: Juan Carlos | Statement: [Juan, commonCompoundName, Juan Carlos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonCompoundName Context triple: [Juan, commonCompoundName, Juan Carlos]
-
A.
commonCompound
Indicates that the two entities share at least one chemical compound in common.
-
B.
commonCompoundNameElement
Indicates that two chemical compound names share a common structural or naming element within their nomenclature.
-
C.
exampleCompoundName
Indicates that something serves as an illustrative or representative compound name used for demonstration or example purposes.
-
D.
usedInCompoundNames
chosen
Indicates that one entity’s name is employed as a component within the compound name of another entity.
-
E.
commonCompoundExample
Indicates that one entity is a typical or illustrative example of a chemical compound associated with another 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_69ee5b48236c81908fe385b6afc4f60b |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f6bbf6e33c819086e5176d64e7a614 |
completed | May 3, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
Created at: April 26, 2026, 8:47 p.m.