Triple
T4831428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bahraini uprising of 2011 |
E107953
|
entity |
| Predicate | arrestsEstimate |
P13732
|
FINISHED |
| Object | thousands arrested |
—
|
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: thousands arrested | Statement: [Bahraini uprising of 2011, arrestsEstimate, thousands arrested]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arrestsEstimate Context triple: [Bahraini uprising of 2011, arrestsEstimate, thousands arrested]
-
A.
numberOfArrests
Indicates the count of times an entity has been arrested.
-
B.
arrests
Indicates that one entity, typically an authority figure, seizes and detains another entity under legal or official power.
-
C.
arrestedFor
Indicates that an authority has taken someone into custody because they are suspected or accused of committing a specified offense or wrongdoing.
-
D.
numberOfPrisonersApproximate
chosen
Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
-
E.
estimatedPrisonerCount
Indicates the estimated number of prisoners associated with a particular context, such as a location, time period, 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c21c7f08190846049d31fdfa144 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.