Triple
T791188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Ensign |
E16917
|
entity |
| Predicate | featuresCross |
P19325
|
FINISHED |
| Object | red St George’s Cross |
—
|
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: red St George’s Cross | Statement: [White Ensign, featuresCross, red St George’s Cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCross Context triple: [White Ensign, featuresCross, red St George’s Cross]
-
A.
featuresCrossoverWith
Indicates that one entity includes or participates in a crossover event or collaboration with another entity.
-
B.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
C.
featuresSupporter
Indicates that one entity serves as a supporter, advocate, or promoter of another entity or its cause.
-
D.
featuresGroup
Indicates that an entity includes or is associated with a specific group as one of its features or components.
-
E.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a79754988190ab494b1c54d6a2a4 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50ef72c819084ffe9f31dbd0262 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a62b497081909503c8d30c7ce1db |
completed | March 1, 2026, 8:48 p.m. |
Created at: March 1, 2026, 7:38 p.m.