Triple
T14941903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert T. Matsui United States Courthouse |
E372550
|
entity |
| Predicate | namedAfterFor |
P63
|
FINISHED |
| Object | public service in the U.S. Congress |
—
|
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: public service in the U.S. Congress | Statement: [Robert T. Matsui United States Courthouse, namedAfterFor, public service in the U.S. Congress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedAfterFor Context triple: [Robert T. Matsui United States Courthouse, namedAfterFor, public service in the U.S. Congress]
-
A.
namedAfter
chosen
Indicates that one entity has been given its name in honor of, or derived from, another entity.
-
B.
namedAfterSince
Indicates that one entity has borne the name of another entity starting from a specific point in time.
-
C.
namedAfterField
Indicates that one entity has been given a name derived from or in honor of another entity, typically a person, place, or thing.
-
D.
namedAfterSuccessor
Indicates that an entity is named after another entity that succeeds or follows it in time, position, or sequence.
-
E.
namedAfterPosition
Indicates that an entity is named after a specific position, role, or rank associated with it.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68c1df0819084c0cd61b207d398 |
completed | April 15, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69de9a588c2c8190b1245a1c406f447c |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:38 a.m.