Triple
T7476299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McCullen v. Coakley |
E176639
|
entity |
| Predicate | speechTypeInvolved |
P29536
|
FINISHED |
| Object | sidewalk counseling |
—
|
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: sidewalk counseling | Statement: [McCullen v. Coakley, speechTypeInvolved, sidewalk counseling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: speechTypeInvolved Context triple: [McCullen v. Coakley, speechTypeInvolved, sidewalk counseling]
-
A.
speechType
chosen
Indicates the specific category or form of spoken or written communication that an utterance or speech act belongs to (e.g., question, statement, command).
-
B.
speakerType
Indicates the role or category of a participant in a communicative act (e.g., narrator, quoted speaker, system voice) within a given context.
-
C.
speechContent
Indicates that one entity expresses, conveys, or contains the spoken or written content associated with another entity’s act of speaking or communication.
-
D.
spokenOn
Indicates that an utterance or speech act occurred at or during a specific time or date.
-
E.
spokenAlong
Indicates that two or more languages are used concurrently or within the same context in a particular place, time, or situation.
- 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_69c69f236ce08190a04d7679f03b29b2 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f4ee23d081908e05658a651661fc |
completed | March 27, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69c6f03d967081908a8e696ff9693b90 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:41 p.m.