Triple
T22462467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monkey 47 |
E555262
|
entity |
| Predicate | hasLabelElement |
P9248
|
FINISHED |
| Object | monkey illustration |
—
|
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: monkey illustration | Statement: [Monkey 47, hasLabelElement, monkey illustration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLabelElement Context triple: [Monkey 47, hasLabelElement, monkey illustration]
-
A.
hasLabel
chosen
Indicates that an entity is associated with a specific textual label or name used to identify or describe it.
-
B.
hasLabelSet
Indicates that an entity is associated with a specific collection or set of labels.
-
C.
isLabeledOn
Indicates that a label, tag, or identifying text is physically or virtually attached to or displayed on an entity.
-
D.
hasSectionLabel
Indicates that a section is associated with a specific label or title used to identify or categorize it.
-
E.
hasLayoutElement
Indicates that one entity includes, contains, or is associated with a specific layout element as part of its structural or visual arrangement.
- 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_69e11e51fdec8190adfdf9f8a6362221 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b80983081908084947b2e31c9d4 |
completed | April 29, 2026, 1:14 a.m. |
| PD | Predicate disambiguation | batch_69e898ad961c819098fd1e46129bddcc |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:48 p.m.