Triple
T1792119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portland City Commissioner Position 3 |
E39518
|
entity |
| Predicate | numberOfMembersInBody |
P3128
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Portland City Commissioner Position 3, numberOfMembersInBody, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMembersInBody Context triple: [Portland City Commissioner Position 3, numberOfMembersInBody, 5]
-
A.
numberOfFullMembers
Indicates the total count of entities that hold full membership status within a specified group or organization.
-
B.
numberOfBoardMembers
chosen
Indicates the total count of individuals who serve as members on a board.
-
C.
numberOfKnownMembers
Indicates the count of members within a group or set whose identities are known or have been explicitly determined.
-
D.
numberOfMembersReturned
Indicates the quantity of members that are provided or yielded as a result of an operation or query.
-
E.
originalNumberOfMembers
Indicates the initial total count of members in a group or organization before any changes such as additions or removals.
- 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab61b6ea188190aab9fb839bf1e367 |
completed | March 6, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69aa61d2f7a8819090301f92d3e358c7 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.