Triple
T1976039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas congressional delegation |
E42913
|
entity |
| Predicate | includesChamber |
P33004
|
FINISHED |
| Object | Senate |
—
|
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: Senate | Statement: [Texas congressional delegation, includesChamber, Senate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesChamber Context triple: [Texas congressional delegation, includesChamber, Senate]
-
A.
appliesToChamber
Indicates that something is relevant or specifically associated with a particular chamber (such as a room, legislative body, or compartment).
-
B.
chamberedFor
Indicates that a firearm is designed or configured to safely accept and fire a specific cartridge or ammunition type in its chamber.
-
C.
belongsToChamber
Indicates that an entity is a member of, or is formally associated with, a specific chamber or legislative body.
-
D.
hasChambersFor
Indicates that one entity contains or provides designated chambers or compartments intended for use by another entity.
-
E.
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.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3f835108190b0709ccf3a487a96 |
completed | March 7, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69abaff9a09c8190a81fa13f4b85bc79 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb09b27e88190bff164040fef6d7e |
completed | March 7, 2026, 4:59 a.m. |
Created at: March 4, 2026, 7:36 p.m.