Triple
T4081628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Terror in Taiwan |
E87488
|
entity |
| Predicate | estimatedNumberOfExecuted |
P19112
|
FINISHED |
| Object | between 3,000 and 4,000 |
—
|
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: between 3,000 and 4,000 | Statement: [White Terror in Taiwan, estimatedNumberOfExecuted, between 3,000 and 4,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedNumberOfExecuted Context triple: [White Terror in Taiwan, estimatedNumberOfExecuted, between 3,000 and 4,000]
-
A.
numberOfExecutions
chosen
Indicates the count of times a particular action, process, or event has been carried out.
-
B.
estimatedNumberOfBlocks
Indicates the approximate count of discrete blocks associated with or involved in the given entity or context.
-
C.
executedDuring
Indicates that an action or event was carried out within the temporal span of another specified event or period.
-
D.
executedWith
Indicates that an action or process was carried out using, accompanied by, or in conjunction with a specified tool, method, or participant.
-
E.
executedIn
Indicates that an action or process is carried out or takes place within a specified location, context, or environment.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc77dab481909bcf197daf2def59 |
completed | March 9, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.