Triple
T37918936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ms. Frizzle |
E945900
|
entity |
| Predicate | fieldTripsType |
P189802
|
FINISHED |
| Object | science-themed field trips |
—
|
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: science-themed field trips | Statement: [Ms. Frizzle, fieldTripsType, science-themed field trips]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldTripsType Context triple: [Ms. Frizzle, fieldTripsType, science-themed field trips]
-
A.
expeditionActivities
Indicates the specific actions, operations, or tasks carried out as part of an expedition.
-
B.
roadTripType
Indicates the specific category or style of a road trip associated with an entity (e.g., scenic, business, long-distance).
-
C.
explorationType
Indicates the specific kind or category of exploration activity associated with an entity or event.
-
D.
travelsFor
Indicates that one entity moves from place to place on behalf of, or for the benefit or purpose of, another entity or objective.
-
E.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
- 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_69f76ef2ebd88190be5229f2621070b3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbca6c066c8190a1599202f341417f |
completed | May 6, 2026, 11:10 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fbc993caa881908c16c3e21efaeef9 |
completed | May 6, 2026, 11:07 p.m. |
Created at: May 3, 2026, 4:20 p.m.