Triple
T19505667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "The woods are lovely, dark and deep," |
E488014
|
entity |
| Predicate | settingEvoked |
P136169
|
FINISHED |
| Object | snowy woods |
—
|
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: snowy woods | Statement: ["The woods are lovely, dark and deep,", settingEvoked, snowy woods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingEvoked Context triple: ["The woods are lovely, dark and deep,", settingEvoked, snowy woods]
-
A.
setting
Indicates the place, time, or context in which an event, action, or interaction occurs.
-
B.
settingControlled
Indicates that one entity regulates, adjusts, or determines the configuration or parameters of another entity.
-
C.
settingAfter
Indicates that one setting or configuration occurs or is applied after another in a sequence or order.
-
D.
designedToEvoke
Indicates that something was intentionally created or arranged in order to elicit a particular reaction, feeling, or response from an audience or observer.
-
E.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635113fdc819098ea0f738d01925c |
completed | April 20, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004d3a708190a1c13c8f644f3926 |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:40 p.m.