Triple
T97056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the Massachusetts Senate |
E1954
|
entity |
| Predicate | chamberType |
P4152
|
FINISHED |
| Object | upper house |
—
|
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: upper house | Statement: [President of the Massachusetts Senate, chamberType, upper house]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chamberType Context triple: [President of the Massachusetts Senate, chamberType, upper house]
-
A.
chamberInvolved
Indicates that a particular chamber (e.g., legislative or judicial body) participates in, is affected by, or plays a role in the referenced event, process, or relationship.
-
B.
numberOfChambers
Indicates the count of distinct chambers or compartments associated with an entity.
-
C.
hasChamber
Indicates that one entity possesses, contains, or is associated with a distinct enclosed space or compartment (a chamber).
-
D.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
-
E.
residenceType
Indicates the kind or category of dwelling or living arrangement associated with an entity.
- F. None of above. chosen
Provenance (4 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a250ca7eec8190b31f7e61f5e3ee1f |
completed | Feb. 28, 2026, 2:19 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.