Triple
T17940486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TTD board |
E448570
|
entity |
| Predicate | canFrame |
P43030
|
FINISHED |
| Object | rules and regulations for TTD administration |
—
|
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: rules and regulations for TTD administration | Statement: [TTD board, canFrame, rules and regulations for TTD administration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canFrame Context triple: [TTD board, canFrame, rules and regulations for TTD administration]
-
A.
canFrameRules
chosen
Indicates that one entity is able to define or establish the governing rules or framework that apply to another entity or context.
-
B.
usesFrame
Indicates that one entity employs, relies on, or is structured around a particular frame, framework, or reference structure provided by another entity.
-
C.
frame
Indicates placing or presenting something within a particular context, structure, or perspective that shapes how it is interpreted.
-
D.
canPass
Indicates that one entity is able or permitted to move through, cross, or successfully traverse another entity or barrier.
-
E.
frameType
Indicates the specific structural or categorical kind of frame associated with an entity or relation.
- 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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4ad95f4608190b1ebb45944218f07 |
completed | April 19, 2026, 10:25 a.m. |
| PD | Predicate disambiguation | batch_69e3f8e713d481908b4a126258c18b63 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:21 a.m.