Triple
T3994861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TOEIC |
E87074
|
entity |
| Predicate | typicalTestDuration |
P53726
|
FINISHED |
| Object | approximately 2 hours for Listening and Reading |
—
|
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: approximately 2 hours for Listening and Reading | Statement: [TOEIC, typicalTestDuration, approximately 2 hours for Listening and Reading]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTestDuration Context triple: [TOEIC, typicalTestDuration, approximately 2 hours for Listening and Reading]
-
A.
typicalDurationDays
Indicates the usual or expected number of days that an associated event, process, or state typically lasts.
-
B.
typicalRecordingDuration
Indicates the usual or standard length of time that something is recorded.
-
C.
typicalScreeningTime
Indicates the usual or standard amount of time allocated for a screening to take place.
-
D.
typicalRuntimePerShort
Indicates the usual or average amount of time it takes to complete a short instance of the referenced activity or process.
-
E.
typicalLength
Indicates the usual or characteristic length associated with an entity or phenomenon.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb81040481909b22e4c445ecae0f |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef8f692008190bf4d637ffc3d3eaa |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefb7f92348190ae35f1d75b0b5d4f |
completed | March 9, 2026, 4:55 p.m. |
Created at: March 9, 2026, 3:34 p.m.