Triple
T11997320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friar Laurence |
E285563
|
entity |
| Predicate | messagePurpose |
P13485
|
FINISHED |
| Object | to inform Romeo of Juliet's feigned death |
—
|
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: to inform Romeo of Juliet's feigned death | Statement: [Friar Laurence, messagePurpose, to inform Romeo of Juliet's feigned death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: messagePurpose Context triple: [Friar Laurence, messagePurpose, to inform Romeo of Juliet's feigned death]
-
A.
intendedMessage
chosen
Indicates that one entity is the message or content that another entity aims or plans to communicate.
-
B.
encodingPurpose
Indicates the reason or intended use for which an encoding is created or applied.
-
C.
purpose
Indicates that one entity exists, is done, or is used in order to achieve, support, or serve the goal, function, or intended outcome of another entity.
-
D.
notationPurpose
Indicates that one notation is used with the specific purpose or function of representing, explaining, or supporting another entity or concept.
-
E.
orderPurpose
Indicates that an order is placed with the specific purpose or intended use of the ordered item or service.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c172788190b92042e9d10a48bf |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.