Triple
T26175085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkish military government after 1980 coup |
E654515
|
entity |
| Predicate | numberOfArrestsEstimate |
P24738
|
FINISHED |
| Object | hundreds of thousands |
—
|
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: hundreds of thousands | Statement: [Turkish military government after 1980 coup, numberOfArrestsEstimate, hundreds of thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfArrestsEstimate Context triple: [Turkish military government after 1980 coup, numberOfArrestsEstimate, hundreds of thousands]
-
A.
numberOfArrests
chosen
Indicates the count of times an entity has been arrested.
-
B.
numberOfConvictions
Indicates the count of times an entity has been formally found guilty of an offense.
-
C.
membersArrestedIn
Indicates that certain members of a group or organization were arrested in a specified location or during a particular event or operation.
-
D.
numberOfIndictedPersonsApproximate
Indicates an approximate count of persons who have been formally indicted in a given context or case.
-
E.
numberOfPrisonersApproximate
Indicates an approximate count of prisoners associated with an entity or situation, rather than an exact number.
- 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_69ee5b45873c81909499203612d05d07 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
Created at: April 26, 2026, 8:37 p.m.