Triple
T3249025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Brave Little Tailor |
E68131
|
entity |
| Predicate | ATUType |
P46820
|
FINISHED |
| Object | ATU 1640 |
—
|
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: ATU 1640 | Statement: [The Brave Little Tailor, ATUType, ATU 1640]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ATUType Context triple: [The Brave Little Tailor, ATUType, ATU 1640]
-
A.
attributeType
Indicates that one entity specifies the kind or category of attribute that characterizes another entity.
-
B.
partAType
Indicates that one entity specifies or denotes the type or category of a particular part (part A) in relation to another entity.
-
C.
associatedUnitType
Indicates that one entity is linked to or characterized by a particular type or category of unit.
-
D.
hasATCClass
Indicates that a drug or medicinal product is assigned to a specific Anatomical Therapeutic Chemical (ATC) classification category.
-
E.
assetType
Indicates the specific category or classification of an asset within a broader asset framework or system.
- 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf3fc3c8819080ac95974581ca0e |
completed | March 8, 2026, 5:17 p.m. |
| PD | Predicate disambiguation | batch_69ada41837e48190933572165be0ca38 |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada525bb2c8190b773efe6d696b6ab |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:09 p.m.