Triple
T34937274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Laughing Man |
E1007611
|
entity |
| Predicate | mainCharactersAgeGroup |
P121688
|
FINISHED |
| Object | boys around nine years old |
—
|
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: boys around nine years old | Statement: [The Laughing Man, mainCharactersAgeGroup, boys around nine years old]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharactersAgeGroup Context triple: [The Laughing Man, mainCharactersAgeGroup, boys around nine years old]
-
A.
hasProtagonistAgeRange
chosen
Indicates that a work’s main character falls within a specified age range.
-
B.
mainCharactersAre
Indicates that the specified entities serve as the primary or central characters in a narrative or work.
-
C.
portraysAgeGroup
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
D.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
E.
characterAgeDescriptor
Indicates how a character’s age is qualitatively described or categorized (e.g., young, middle-aged, elderly) rather than given as a specific number.
- 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_69f76dc513fc819084a1ff52abbfa5bc |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd35d108908190b79b1e8e6bbd62aa |
completed | May 8, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69fd34cb46108190b43c3b7f67ec4cd4 |
completed | May 8, 2026, 12:56 a.m. |
Created at: May 3, 2026, 4 p.m.