Triple
T20179382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Twain Zephyr |
E492684
|
entity |
| Predicate | namedForProfessionOfNamesake |
P133817
|
FINISHED |
| Object | author |
—
|
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: author | Statement: [Mark Twain Zephyr, namedForProfessionOfNamesake, author]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForProfessionOfNamesake Context triple: [Mark Twain Zephyr, namedForProfessionOfNamesake, author]
-
A.
isNamedAfterOccupation
Indicates that an entity’s name is derived from or based on a particular occupation or profession.
-
B.
usedAsNamesakeFor
Indicates that one entity serves as the source or inspiration for the name given to another entity.
-
C.
namesakeOccupation
Indicates that one entity’s occupation is the same as, or derived from, the occupation associated with the other entity’s namesake.
-
D.
namedAccordingTo
Indicates that one entity is given a name that follows, references, or is derived from another entity or source.
-
E.
notableNamesakeOccupation
chosen
Indicates that an entity is named after a notable person whose occupation or professional role is specified by the related value.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e668edf27881909820f9103e72533e |
completed | April 20, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:36 p.m.