Triple
T29098039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Whatsit |
E735062
|
entity |
| Predicate | helpsCharacterRescue |
P134021
|
FINISHED |
| Object | Dr. Alex Murry |
—
|
NE NERFINISHED |
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: Dr. Alex Murry | Statement: [Mrs. Whatsit, helpsCharacterRescue, Dr. Alex Murry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helpsCharacterRescue Context triple: [Mrs. Whatsit, helpsCharacterRescue, Dr. Alex Murry]
-
A.
seeksToRescue
Indicates an entity’s intention or effort to save or free another entity from danger, harm, or an undesirable situation.
-
B.
rescuesWith
Indicates that one entity saves or frees another entity from danger, harm, or captivity using a particular means, tool, or method.
-
C.
usedMeansToRescue
Indicates that one entity employed a particular method, tool, or means in order to carry out a rescue.
-
D.
roleInRescue
Indicates the specific function or responsibility an entity has within a rescue operation or event.
-
E.
involvedRescue
chosen
Indicates that an entity participated in or contributed to a rescue operation or act of saving someone or something from danger.
- 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_69f05b0ed66481908f2e864fa550d2f1 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6618344c08190a3c918a41a871381 |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 11:10 a.m.