Triple
T4191732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Friesland |
E89051
|
entity |
| Predicate | numberOfSymbols |
P37173
|
FINISHED |
| Object | seven |
—
|
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: seven | Statement: [Flag of Friesland, numberOfSymbols, seven]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSymbols Context triple: [Flag of Friesland, numberOfSymbols, seven]
-
A.
numberOfSigns
chosen
Indicates the quantity of signs associated with or present in relation to a given entity or context.
-
B.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
C.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
D.
numberOfStrings
Indicates the quantity of strings associated with or contained by an entity.
-
E.
numberOfCommonUseCharacters
Indicates the count of characters that are shared in common between two entities’ representations or strings.
- 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_69aed9569a4481908b6c1fcec2a11e21 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af04b009dc8190abda3f149a5b16fa |
completed | March 9, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69af01935064819096b7619f42e164dd |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:46 p.m.