Triple
T10646582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Bicolor |
E250849
|
entity |
| Predicate | refersToKitCharacteristic |
P56672
|
FINISHED |
| Object | two-colored kit |
—
|
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: two-colored kit | Statement: [La Bicolor, refersToKitCharacteristic, two-colored kit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToKitCharacteristic Context triple: [La Bicolor, refersToKitCharacteristic, two-colored kit]
-
A.
hasCharacteristic
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
-
B.
describesCharacteristicOf
chosen
Indicates that one entity expresses or specifies a characteristic, feature, or property of another entity.
-
C.
eraCharacteristic
Indicates that a particular quality, feature, or attribute is characteristic of, or typically associated with, a given historical or temporal era.
-
D.
codeCharacteristic
Indicates that one piece of code possesses a specific property, feature, or quality in relation to another referenced aspect.
-
E.
dataCharacteristic
Indicates that one entity specifies a property, attribute, or feature that characterizes a given piece of data.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfe1cd6081909df9e4dc0fda1f0b |
completed | April 8, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69d6dd83b114819098e84dc658e82d7e |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:05 p.m.