Triple
T37974664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dame Ragnelle |
E947387
|
entity |
| Predicate | conditionOfRescue |
P189819
|
FINISHED |
| Object | marriage to Sir Gawain |
—
|
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: marriage to Sir Gawain | Statement: [Dame Ragnelle, conditionOfRescue, marriage to Sir Gawain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conditionOfRescue Context triple: [Dame Ragnelle, conditionOfRescue, marriage to Sir Gawain]
-
A.
typeOfRescue
Indicates the specific method or category of rescue operation performed in a rescue event.
-
B.
usedMeansToRescue
Indicates that one entity employed a particular method, tool, or means in order to carry out a rescue.
-
C.
seeksToRescue
Indicates an entity’s intention or effort to save or free another entity from danger, harm, or an undesirable situation.
-
D.
statusBeforeRescue
Indicates the condition or situation an entity was in prior to being rescued.
-
E.
statusAfterRescue
Indicates the condition or state an entity is in following a rescue event or operation.
- 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_69f76ef7db908190bba6086673a32300 |
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.