Triple
T32932515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin W. Dixon |
E842434
|
entity |
| Predicate | notARealPerson |
P175410
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Franklin W. Dixon, notARealPerson, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notARealPerson Context triple: [Franklin W. Dixon, notARealPerson, true]
-
A.
notRealNameOf
Indicates that the referenced name is not the entity’s actual or official name (e.g., it is false, fabricated, or otherwise not the real name of that entity).
-
B.
realPerson
Indicates that the referenced entity corresponds to an actual human individual, as opposed to a fictional, anonymous, or non-human entity.
-
C.
notHumanInStory
Indicates that the referenced entity does not appear as a human character within the context of the story.
-
D.
featuresRealPersonAsHimself
Indicates that a real person appears in the work portraying themself rather than a fictional character.
-
E.
nonHumanCharacter
Indicates that the character involved in the relation is not a human being (e.g., an animal, creature, AI, or other non-human entity).
- 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_69f34948adfc8190a937f1f622783c0b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d1d916f881909575c2b22c416a5b |
completed | May 3, 2026, 4:40 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe5f93c8190995c53dbbe380a32 |
completed | May 3, 2026, 4:32 a.m. |
| PDg | Predicate description generation | batch_69f6d0d331dc8190be5aa6bfc6365e67 |
completed | May 3, 2026, 4:36 a.m. |
Created at: May 1, 2026, 1:20 a.m.