Triple
T34997215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Croatian checkerboard |
E1009571
|
entity |
| Predicate | fieldCount |
P36398
|
FINISHED |
| Object | 25 squares |
—
|
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: 25 squares | Statement: [Croatian checkerboard, fieldCount, 25 squares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldCount Context triple: [Croatian checkerboard, fieldCount, 25 squares]
-
A.
hasNumberOfFields
chosen
Indicates the specific count of fields or distinct data elements that an entity possesses.
-
B.
fieldSize
Indicates the magnitude or dimensions of a field associated with an entity or context.
-
C.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
D.
numberOfFieldPeriods
Indicates the total count of distinct field periods associated with or occurring within a given context or entity.
-
E.
numberOfAttributes
Indicates the total count of distinct attributes or properties associated with a given entity or object.
- 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_69f76dca50dc8190b71f39defe186be8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7979a073881909a4fde2558e6b6f3 |
completed | May 3, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:01 p.m.