Triple
T29097995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Murry |
E735061
|
entity |
| Predicate | isCharacterRole |
P136950
|
FINISHED |
| Object | mother of Meg Murry |
—
|
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: mother of Meg Murry | Statement: [Mrs. Murry, isCharacterRole, mother of Meg Murry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCharacterRole Context triple: [Mrs. Murry, isCharacterRole, mother of Meg Murry]
-
A.
hasHumanCharacterRole
chosen
Indicates that an entity is assigned a role or function specifically associated with a human character within a context such as a story, performance, or representation.
-
B.
actorRole
Indicates that an entity participates in an event or action in a specific capacity or function (such as performer, initiator, or responsible party).
-
C.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
D.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
E.
actingRoleType
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
- 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.