Triple
T2408633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governor Moonbeam |
E50333
|
entity |
| Predicate | associatedWithTermCount |
P9908
|
FINISHED |
| Object | four-term governorship of California |
—
|
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: four-term governorship of California | Statement: [Governor Moonbeam, associatedWithTermCount, four-term governorship of California]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithTermCount Context triple: [Governor Moonbeam, associatedWithTermCount, four-term governorship of California]
-
A.
associatedWithRank
Indicates a relationship where an entity is linked to a specific rank, level, or hierarchical position.
-
B.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
-
C.
associatedWithText
Indicates that an entity has a contextual or semantic connection to a specific piece of text.
-
D.
hasNumberOfTerms
chosen
Indicates the quantity of distinct terms or elements associated with a given entity or expression.
-
E.
associatedWithCondition
Indicates that an entity has a relevant connection or linkage to a particular condition (such as a disease, state, or circumstance), without specifying the nature or strength of that connection.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abceab9ce881909ae0a2f34515c11e |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5a530e8819094105aa92dfaf6b3 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:58 p.m.