Triple
T3672968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rushmore |
E77920
|
entity |
| Predicate | hasTitleCharacterOccupation |
P38167
|
FINISHED |
| Object | student |
—
|
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: student | Statement: [Rushmore, hasTitleCharacterOccupation, student]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleCharacterOccupation Context triple: [Rushmore, hasTitleCharacterOccupation, student]
-
A.
titleOrRole
chosen
Indicates that one entity serves as the title, position, or role held or described by another entity.
-
B.
followsCharacterOccupation
Indicates that one character’s occupation or job role comes after or succeeds another character’s occupation in a sequence or progression.
-
C.
hasTitleCharacterRelation
Indicates a relationship where a title (such as a work or publication) is associated with or linked to a specific character appearing in it.
-
D.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
E.
workTitle
Indicates the formal title or name of a work (such as a book, artwork, or composition) 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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc42f82548190b4d5f0fe7250decb |
completed | March 8, 2026, 6:47 p.m. |
| PD | Predicate disambiguation | batch_69adb84a20288190a092e4a1b045fe3f |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:25 p.m.