Triple
T29128995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miguel Montoya |
E738316
|
entity |
| Predicate | associatedWorkByNameSimilarity |
P922
|
FINISHED |
| Object | The Princess Bride |
E1209772
|
NE 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: The Princess Bride | Statement: [Miguel Montoya, associatedWorkByNameSimilarity, The Princess Bride]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWorkByNameSimilarity Context triple: [Miguel Montoya, associatedWorkByNameSimilarity, The Princess Bride]
-
A.
associatedWork
chosen
Indicates that there exists a related or connected work (such as a publication, creative piece, or project) that is meaningfully linked to the subject.
-
B.
associatedWithWorkOf
Indicates that one entity has a connection or involvement with the work, creation, or output produced by another entity.
-
C.
associatedWithInWork
Indicates that two entities are connected or related to each other within the context of a particular work or project.
-
D.
relatedWorkByKey
Indicates a relationship where one work is linked or associated to another work identified by a specific key or identifier.
-
E.
relatedWorkBySubject
Indicates a relationship where one work is connected to another through sharing the same subject or topic.
- F. None of above.
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_69f07cb29cdc8190afa55444553de60c |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_6a030f1480148190a5e8c8926ded252c |
completed | May 12, 2026, 11:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2550565f4081908d73740f8dd8d746 |
completed | June 7, 2026, 11:04 a.m. |
| PD | Predicate disambiguation | batch_6a030e7f5fa481909696733defefcc20 |
completed | May 12, 2026, 11:26 a.m. |
Created at: April 28, 2026, 11:30 a.m.