Triple
T29555052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 100 Tourist Sites of Bulgaria |
E749884
|
entity |
| Predicate | numberOfItemsOriginally |
P19248
|
FINISHED |
| Object | 100 |
—
|
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: 100 | Statement: [100 Tourist Sites of Bulgaria, numberOfItemsOriginally, 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfItemsOriginally Context triple: [100 Tourist Sites of Bulgaria, numberOfItemsOriginally, 100]
-
A.
estimatedNumberOfItems
Indicates the approximate count or quantity of items associated with the subject, typically when the exact number is unknown or uncertain.
-
B.
numberOfUnits
chosen
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
C.
mainQuantity
Indicates that the associated value represents the primary or principal quantity in a given context or relationship.
-
D.
estimatedNumberOfRemains
Indicates the approximate count of human or other remains associated with an entity, based on estimation rather than an exact measurement.
-
E.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
- 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_69f0bd4919e48190942b2a13d5b97d03 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_6a0008225cc081909ff1fd0639859dc4 |
completed | May 10, 2026, 4:22 a.m. |
| PD | Predicate disambiguation | batch_6a0007bac5d8819098aff8031d4abe5d |
completed | May 10, 2026, 4:21 a.m. |
Created at: April 28, 2026, 5:15 p.m.